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You searched for subject:(Gene prediction). Showing records 1 – 30 of 90 total matches.

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Brno University of Technology

1. Nykrýnová, Markéta. Metody predikce genů v prokaryotických genomech .

Degree: 2016, Brno University of Technology

 Tato bakalářská práce se zabývá metodami predikce genů v prokaryotických organismech. V první části je popsána prokaryotická buňka včetně genomu, exprese genetické informace a rozdělení… (more)

Subjects/Keywords: predikce genů; prokaryota; gen; gene prediction; prokaryote; gene

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Nykrýnová, M. (2016). Metody predikce genů v prokaryotických genomech . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/61527

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Nykrýnová, Markéta. “Metody predikce genů v prokaryotických genomech .” 2016. Thesis, Brno University of Technology. Accessed December 12, 2019. http://hdl.handle.net/11012/61527.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Nykrýnová, Markéta. “Metody predikce genů v prokaryotických genomech .” 2016. Web. 12 Dec 2019.

Vancouver:

Nykrýnová M. Metody predikce genů v prokaryotických genomech . [Internet] [Thesis]. Brno University of Technology; 2016. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/11012/61527.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nykrýnová M. Metody predikce genů v prokaryotických genomech . [Thesis]. Brno University of Technology; 2016. Available from: http://hdl.handle.net/11012/61527

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Southern Mississippi

2. Zhao, Chenguang. GOGO: An Improved Algorithm to Measure the Semantic Similarity Between Gene Ontology Terms.

Degree: MS, 2019, University of Southern Mississippi

  Measuring the semantic similarity between Gene Ontology (GO) terms is an essential step in functional bioinformatics research. We implemented a software named GOGO for… (more)

Subjects/Keywords: semantic similarity; functional similarity; gene ontology; gene function prediction; gene cluster; Bioinformatics; Theory and Algorithms

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APA (6th Edition):

Zhao, C. (2019). GOGO: An Improved Algorithm to Measure the Semantic Similarity Between Gene Ontology Terms. (Masters Thesis). University of Southern Mississippi. Retrieved from https://aquila.usm.edu/masters_theses/626

Chicago Manual of Style (16th Edition):

Zhao, Chenguang. “GOGO: An Improved Algorithm to Measure the Semantic Similarity Between Gene Ontology Terms.” 2019. Masters Thesis, University of Southern Mississippi. Accessed December 12, 2019. https://aquila.usm.edu/masters_theses/626.

MLA Handbook (7th Edition):

Zhao, Chenguang. “GOGO: An Improved Algorithm to Measure the Semantic Similarity Between Gene Ontology Terms.” 2019. Web. 12 Dec 2019.

Vancouver:

Zhao C. GOGO: An Improved Algorithm to Measure the Semantic Similarity Between Gene Ontology Terms. [Internet] [Masters thesis]. University of Southern Mississippi; 2019. [cited 2019 Dec 12]. Available from: https://aquila.usm.edu/masters_theses/626.

Council of Science Editors:

Zhao C. GOGO: An Improved Algorithm to Measure the Semantic Similarity Between Gene Ontology Terms. [Masters Thesis]. University of Southern Mississippi; 2019. Available from: https://aquila.usm.edu/masters_theses/626


University of Manchester

3. Kabir, Mitra. Prediction of Mammalian Essential Genes based on Sequence and Functional Features.

Degree: 2017, University of Manchester

Essential genes are those whose presence is imperative for an organism’s survival, whereas the functions of non–essential genes may be useful but not critical. Abnormal… (more)

Subjects/Keywords: Mammalian Gene Essentiality; Machine Learning; Random Forest; Gene Prediction; Gene Duplication; Feature Selection; Gene co-expression; Morphological Hourglass Model

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APA (6th Edition):

Kabir, M. (2017). Prediction of Mammalian Essential Genes based on Sequence and Functional Features. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307584

Chicago Manual of Style (16th Edition):

Kabir, Mitra. “Prediction of Mammalian Essential Genes based on Sequence and Functional Features.” 2017. Doctoral Dissertation, University of Manchester. Accessed December 12, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307584.

MLA Handbook (7th Edition):

Kabir, Mitra. “Prediction of Mammalian Essential Genes based on Sequence and Functional Features.” 2017. Web. 12 Dec 2019.

Vancouver:

Kabir M. Prediction of Mammalian Essential Genes based on Sequence and Functional Features. [Internet] [Doctoral dissertation]. University of Manchester; 2017. [cited 2019 Dec 12]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307584.

Council of Science Editors:

Kabir M. Prediction of Mammalian Essential Genes based on Sequence and Functional Features. [Doctoral Dissertation]. University of Manchester; 2017. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307584


University of Manchester

4. Kabir, Mitra. Prediction of mammalian essential genes based on sequence and functional features.

Degree: PhD, 2017, University of Manchester

 Essential genes are those whose presence is imperative for an organism's survival, whereas the functions of non-essential genes may be useful but not critical. Abnormal… (more)

Subjects/Keywords: 572; Morphological Hourglass Model; Gene Duplication; Gene Prediction; Feature Selection; Machine Learning; Mammalian Gene Essentiality; Random Forest; Gene co-expression

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APA (6th Edition):

Kabir, M. (2017). Prediction of mammalian essential genes based on sequence and functional features. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/prediction-of-mammalian-essential-genes-based-on-sequence-and-functional-features(cf8eeed5-c2b3-47c3-9a8f-2cc290c90d56).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713584

Chicago Manual of Style (16th Edition):

Kabir, Mitra. “Prediction of mammalian essential genes based on sequence and functional features.” 2017. Doctoral Dissertation, University of Manchester. Accessed December 12, 2019. https://www.research.manchester.ac.uk/portal/en/theses/prediction-of-mammalian-essential-genes-based-on-sequence-and-functional-features(cf8eeed5-c2b3-47c3-9a8f-2cc290c90d56).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713584.

MLA Handbook (7th Edition):

Kabir, Mitra. “Prediction of mammalian essential genes based on sequence and functional features.” 2017. Web. 12 Dec 2019.

Vancouver:

Kabir M. Prediction of mammalian essential genes based on sequence and functional features. [Internet] [Doctoral dissertation]. University of Manchester; 2017. [cited 2019 Dec 12]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/prediction-of-mammalian-essential-genes-based-on-sequence-and-functional-features(cf8eeed5-c2b3-47c3-9a8f-2cc290c90d56).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713584.

Council of Science Editors:

Kabir M. Prediction of mammalian essential genes based on sequence and functional features. [Doctoral Dissertation]. University of Manchester; 2017. Available from: https://www.research.manchester.ac.uk/portal/en/theses/prediction-of-mammalian-essential-genes-based-on-sequence-and-functional-features(cf8eeed5-c2b3-47c3-9a8f-2cc290c90d56).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713584


University of Gothenburg / Göteborgs Universitet

5. Davila Lopez, Marcela. Evolution of protein and non-coding RNA genes studied with comparative genomics.

Degree: 2010, University of Gothenburg / Göteborgs Universitet

 The identification of protein and non-coding RNA (ncRNA) genes is one important step in the analysis of a genome. This thesis focuses on the identification… (more)

Subjects/Keywords: Bioinformatics; evolution; non-coding RNA; gene prediction; gene order; bidirectional promoter; homologue prediction; secondary structure; RNAse P; RNase MRP

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APA (6th Edition):

Davila Lopez, M. (2010). Evolution of protein and non-coding RNA genes studied with comparative genomics. (Thesis). University of Gothenburg / Göteborgs Universitet. Retrieved from http://hdl.handle.net/2077/23816

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Davila Lopez, Marcela. “Evolution of protein and non-coding RNA genes studied with comparative genomics.” 2010. Thesis, University of Gothenburg / Göteborgs Universitet. Accessed December 12, 2019. http://hdl.handle.net/2077/23816.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Davila Lopez, Marcela. “Evolution of protein and non-coding RNA genes studied with comparative genomics.” 2010. Web. 12 Dec 2019.

Vancouver:

Davila Lopez M. Evolution of protein and non-coding RNA genes studied with comparative genomics. [Internet] [Thesis]. University of Gothenburg / Göteborgs Universitet; 2010. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/2077/23816.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Davila Lopez M. Evolution of protein and non-coding RNA genes studied with comparative genomics. [Thesis]. University of Gothenburg / Göteborgs Universitet; 2010. Available from: http://hdl.handle.net/2077/23816

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brigham Young University

6. Chan, Heather Y. Gene Network Inference and Expression Prediction Using Recurrent Neural Networks and Evolutionary Algorithms.

Degree: MS, 2010, Brigham Young University

 We demonstrate the success of recurrent neural networks in gene network inference and expression prediction using a hybrid of particle swarm optimization and differential evolution… (more)

Subjects/Keywords: genetic network modeling; gene network inference; gene expression prediction; recurrent networks; evolutionary algorithms; time series prediction; Computer Sciences

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APA (6th Edition):

Chan, H. Y. (2010). Gene Network Inference and Expression Prediction Using Recurrent Neural Networks and Evolutionary Algorithms. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3647&context=etd

Chicago Manual of Style (16th Edition):

Chan, Heather Y. “Gene Network Inference and Expression Prediction Using Recurrent Neural Networks and Evolutionary Algorithms.” 2010. Masters Thesis, Brigham Young University. Accessed December 12, 2019. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3647&context=etd.

MLA Handbook (7th Edition):

Chan, Heather Y. “Gene Network Inference and Expression Prediction Using Recurrent Neural Networks and Evolutionary Algorithms.” 2010. Web. 12 Dec 2019.

Vancouver:

Chan HY. Gene Network Inference and Expression Prediction Using Recurrent Neural Networks and Evolutionary Algorithms. [Internet] [Masters thesis]. Brigham Young University; 2010. [cited 2019 Dec 12]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3647&context=etd.

Council of Science Editors:

Chan HY. Gene Network Inference and Expression Prediction Using Recurrent Neural Networks and Evolutionary Algorithms. [Masters Thesis]. Brigham Young University; 2010. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3647&context=etd


University of Akron

7. Macholan, Robert Daniel. Analysis of Gene Expression Data for Gene Ontology Based Protein Function Prediction.

Degree: MS, Computer Science, 2011, University of Akron

 A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the… (more)

Subjects/Keywords: Bioinformatics; Computer Science; Gene Expression; Gene Ontology; Protein Function; Prediction; Slope Matrix

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APA (6th Edition):

Macholan, R. D. (2011). Analysis of Gene Expression Data for Gene Ontology Based Protein Function Prediction. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1301529255

Chicago Manual of Style (16th Edition):

Macholan, Robert Daniel. “Analysis of Gene Expression Data for Gene Ontology Based Protein Function Prediction.” 2011. Masters Thesis, University of Akron. Accessed December 12, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1301529255.

MLA Handbook (7th Edition):

Macholan, Robert Daniel. “Analysis of Gene Expression Data for Gene Ontology Based Protein Function Prediction.” 2011. Web. 12 Dec 2019.

Vancouver:

Macholan RD. Analysis of Gene Expression Data for Gene Ontology Based Protein Function Prediction. [Internet] [Masters thesis]. University of Akron; 2011. [cited 2019 Dec 12]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1301529255.

Council of Science Editors:

Macholan RD. Analysis of Gene Expression Data for Gene Ontology Based Protein Function Prediction. [Masters Thesis]. University of Akron; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1301529255


Georgia Tech

8. Zhu, Wenhan. Improvement of ab initio methods of gene prediction in genomic and metagenomic sequences.

Degree: PhD, Biology, 2010, Georgia Tech

 A metagenome originated from a shotgun sequencing of a microbial community is a heterogeneous mixture of rather short sequences. A vast majority of microbial species… (more)

Subjects/Keywords: Codon usage; Hidden Markov model; Gene prediction; GeneMark; Metagenomics; Gene finding; Markov processes; Genetics

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APA (6th Edition):

Zhu, W. (2010). Improvement of ab initio methods of gene prediction in genomic and metagenomic sequences. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/33869

Chicago Manual of Style (16th Edition):

Zhu, Wenhan. “Improvement of ab initio methods of gene prediction in genomic and metagenomic sequences.” 2010. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/33869.

MLA Handbook (7th Edition):

Zhu, Wenhan. “Improvement of ab initio methods of gene prediction in genomic and metagenomic sequences.” 2010. Web. 12 Dec 2019.

Vancouver:

Zhu W. Improvement of ab initio methods of gene prediction in genomic and metagenomic sequences. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/33869.

Council of Science Editors:

Zhu W. Improvement of ab initio methods of gene prediction in genomic and metagenomic sequences. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/33869

9. Harris, Zachary Noel. Transcriptome Profiling and Long Non-Coding Rna Identification in Grapevine.

Degree: MSin Biology, Biology, 2017, Missouri State University

 Next-generation sequencing technologies have provided access to vast quantities of nucleic acid sequence data. The resulting wealth of information enables biologists to address complex biological… (more)

Subjects/Keywords: transcriptome; genome annotation; grapevine; lncRNA; computational biology; gene prediction; Biology

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APA (6th Edition):

Harris, Z. N. (2017). Transcriptome Profiling and Long Non-Coding Rna Identification in Grapevine. (Masters Thesis). Missouri State University. Retrieved from https://bearworks.missouristate.edu/theses/3183

Chicago Manual of Style (16th Edition):

Harris, Zachary Noel. “Transcriptome Profiling and Long Non-Coding Rna Identification in Grapevine.” 2017. Masters Thesis, Missouri State University. Accessed December 12, 2019. https://bearworks.missouristate.edu/theses/3183.

MLA Handbook (7th Edition):

Harris, Zachary Noel. “Transcriptome Profiling and Long Non-Coding Rna Identification in Grapevine.” 2017. Web. 12 Dec 2019.

Vancouver:

Harris ZN. Transcriptome Profiling and Long Non-Coding Rna Identification in Grapevine. [Internet] [Masters thesis]. Missouri State University; 2017. [cited 2019 Dec 12]. Available from: https://bearworks.missouristate.edu/theses/3183.

Council of Science Editors:

Harris ZN. Transcriptome Profiling and Long Non-Coding Rna Identification in Grapevine. [Masters Thesis]. Missouri State University; 2017. Available from: https://bearworks.missouristate.edu/theses/3183


Drexel University

10. Yok, Non G. New approaches to improving organisms detection and gene prediction in metagenomes.

Degree: 2011, Drexel University

This thesis investigates microorganism detection and gene prediction on the DNA level from environmental samples such as air, water, soil, and the human body. In… (more)

Subjects/Keywords: Electric engineering; Molecular microbiology; Microorganisms – Molecular aspects; Gene prediction

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APA (6th Edition):

Yok, N. G. (2011). New approaches to improving organisms detection and gene prediction in metagenomes. (Thesis). Drexel University. Retrieved from http://hdl.handle.net/1860/3541

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yok, Non G. “New approaches to improving organisms detection and gene prediction in metagenomes.” 2011. Thesis, Drexel University. Accessed December 12, 2019. http://hdl.handle.net/1860/3541.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yok, Non G. “New approaches to improving organisms detection and gene prediction in metagenomes.” 2011. Web. 12 Dec 2019.

Vancouver:

Yok NG. New approaches to improving organisms detection and gene prediction in metagenomes. [Internet] [Thesis]. Drexel University; 2011. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1860/3541.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yok NG. New approaches to improving organisms detection and gene prediction in metagenomes. [Thesis]. Drexel University; 2011. Available from: http://hdl.handle.net/1860/3541

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Princeton University

11. Goya, Jonathan Kenshin. Post-transcriptional regulation of protein abundance and function .

Degree: PhD, 2018, Princeton University

 Animals, plants, and other multicellular organisms all begin life with a static genome in a single cell and grow to a diverse array of cell… (more)

Subjects/Keywords: Gene function prediction; Proteomics; Stable isotope labeling; Tissue specificity

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APA (6th Edition):

Goya, J. K. (2018). Post-transcriptional regulation of protein abundance and function . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01sj139471c

Chicago Manual of Style (16th Edition):

Goya, Jonathan Kenshin. “Post-transcriptional regulation of protein abundance and function .” 2018. Doctoral Dissertation, Princeton University. Accessed December 12, 2019. http://arks.princeton.edu/ark:/88435/dsp01sj139471c.

MLA Handbook (7th Edition):

Goya, Jonathan Kenshin. “Post-transcriptional regulation of protein abundance and function .” 2018. Web. 12 Dec 2019.

Vancouver:

Goya JK. Post-transcriptional regulation of protein abundance and function . [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2019 Dec 12]. Available from: http://arks.princeton.edu/ark:/88435/dsp01sj139471c.

Council of Science Editors:

Goya JK. Post-transcriptional regulation of protein abundance and function . [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp01sj139471c


Princeton University

12. Homilius, Max. Network-Based Prioritization of Disease Genes, Animal Models, and Drug Targets .

Degree: PhD, 2018, Princeton University

 In living organisms, biomolecules interact in complex molecular networks that underlie cell function and whose dysregulation leads to disease. These networks thus provide a key… (more)

Subjects/Keywords: animal models; disease-gene prediction; drug targets; functional networks

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APA (6th Edition):

Homilius, M. (2018). Network-Based Prioritization of Disease Genes, Animal Models, and Drug Targets . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01mg74qp881

Chicago Manual of Style (16th Edition):

Homilius, Max. “Network-Based Prioritization of Disease Genes, Animal Models, and Drug Targets .” 2018. Doctoral Dissertation, Princeton University. Accessed December 12, 2019. http://arks.princeton.edu/ark:/88435/dsp01mg74qp881.

MLA Handbook (7th Edition):

Homilius, Max. “Network-Based Prioritization of Disease Genes, Animal Models, and Drug Targets .” 2018. Web. 12 Dec 2019.

Vancouver:

Homilius M. Network-Based Prioritization of Disease Genes, Animal Models, and Drug Targets . [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2019 Dec 12]. Available from: http://arks.princeton.edu/ark:/88435/dsp01mg74qp881.

Council of Science Editors:

Homilius M. Network-Based Prioritization of Disease Genes, Animal Models, and Drug Targets . [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp01mg74qp881


Georgia Tech

13. Phan, John H. Biomarker discovery and clinical outcome prediction using knowledge based-bioinformatics.

Degree: PhD, Biomedical Engineering, 2009, Georgia Tech

 Advances in high-throughput genomic and proteomic technology have led to a growing interest in cancer biomarkers. These biomarkers can potentially improve the accuracy of cancer… (more)

Subjects/Keywords: Feature selection; Gene expression profiling; Biomarker identification; Clinical outcome prediction; Knowledge based; Bioinformatics; Biochemical markers; Gene expression

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APA (6th Edition):

Phan, J. H. (2009). Biomarker discovery and clinical outcome prediction using knowledge based-bioinformatics. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/33855

Chicago Manual of Style (16th Edition):

Phan, John H. “Biomarker discovery and clinical outcome prediction using knowledge based-bioinformatics.” 2009. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/33855.

MLA Handbook (7th Edition):

Phan, John H. “Biomarker discovery and clinical outcome prediction using knowledge based-bioinformatics.” 2009. Web. 12 Dec 2019.

Vancouver:

Phan JH. Biomarker discovery and clinical outcome prediction using knowledge based-bioinformatics. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/33855.

Council of Science Editors:

Phan JH. Biomarker discovery and clinical outcome prediction using knowledge based-bioinformatics. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/33855

14. Lin, Yunxi. Genome assembly and annotation of a haptophyte .

Degree: 2013, California State University – San Marcos

 The genome of a haptophyte was sequenced using the next-generation sequencing (NGS) technology. 18 billion base pairs high quality sequence data from NGS platform, HiSeq… (more)

Subjects/Keywords: bioinformatics; next-generation sequencing; de novo assembly; gene annotation; evidence based alignment; ab initio and evidence-driven gene prediction

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APA (6th Edition):

Lin, Y. (2013). Genome assembly and annotation of a haptophyte . (Thesis). California State University – San Marcos. Retrieved from http://hdl.handle.net/10211.8/531

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lin, Yunxi. “Genome assembly and annotation of a haptophyte .” 2013. Thesis, California State University – San Marcos. Accessed December 12, 2019. http://hdl.handle.net/10211.8/531.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lin, Yunxi. “Genome assembly and annotation of a haptophyte .” 2013. Web. 12 Dec 2019.

Vancouver:

Lin Y. Genome assembly and annotation of a haptophyte . [Internet] [Thesis]. California State University – San Marcos; 2013. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/10211.8/531.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin Y. Genome assembly and annotation of a haptophyte . [Thesis]. California State University – San Marcos; 2013. Available from: http://hdl.handle.net/10211.8/531

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

15. Bahurek, Tomáš. Detekce genů v DNA sekvencích .

Degree: 2011, Brno University of Technology

 Tato práce se věnuje problematice detekce genů v DNA sekvencích. Vysvětluje spůsob uložení informace v DNA sekvencích, poskytuje přehled některých metod pro detekci genů, konkrétně… (more)

Subjects/Keywords: molekulární biologie; DNA; detekce genů; génová predikce; prokaryoty; molecular biology; DNA; gene detection; gene prediction; prokaryotes

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APA (6th Edition):

Bahurek, T. (2011). Detekce genů v DNA sekvencích . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55805

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bahurek, Tomáš. “Detekce genů v DNA sekvencích .” 2011. Thesis, Brno University of Technology. Accessed December 12, 2019. http://hdl.handle.net/11012/55805.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bahurek, Tomáš. “Detekce genů v DNA sekvencích .” 2011. Web. 12 Dec 2019.

Vancouver:

Bahurek T. Detekce genů v DNA sekvencích . [Internet] [Thesis]. Brno University of Technology; 2011. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/11012/55805.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bahurek T. Detekce genů v DNA sekvencích . [Thesis]. Brno University of Technology; 2011. Available from: http://hdl.handle.net/11012/55805

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of New Orleans

16. Baribault, Carl. Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification.

Degree: PhD, Computer Science, 2009, University of New Orleans

 Using a generalized-clique hidden Markov model (HMM) as the starting point for a eukaryotic gene finder, the objective here is to strengthen the signal information… (more)

Subjects/Keywords: hidden Markov model; HMM; GHMM; gene finding; gene prediction

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APA (6th Edition):

Baribault, C. (2009). Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification. (Doctoral Dissertation). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/1098

Chicago Manual of Style (16th Edition):

Baribault, Carl. “Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification.” 2009. Doctoral Dissertation, University of New Orleans. Accessed December 12, 2019. https://scholarworks.uno.edu/td/1098.

MLA Handbook (7th Edition):

Baribault, Carl. “Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification.” 2009. Web. 12 Dec 2019.

Vancouver:

Baribault C. Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification. [Internet] [Doctoral dissertation]. University of New Orleans; 2009. [cited 2019 Dec 12]. Available from: https://scholarworks.uno.edu/td/1098.

Council of Science Editors:

Baribault C. Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification. [Doctoral Dissertation]. University of New Orleans; 2009. Available from: https://scholarworks.uno.edu/td/1098

17. Ferraz Néto, Karla. Análise gênica de comorbidades a partir da integração de dados epidemiológicos.

Degree: Mestrado, Bioinformática, 2014, University of São Paulo

A identificação de genes responsáveis por doenças humanas pode fornecer conhecimentos sobre mecanismos patológicos e psicológicos que são essenciais para o desenvolvimento de novos diagnósticos… (more)

Subjects/Keywords: comorbidade; comorbidity; data integration; gene prediction; integração de dados; predição de genes

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ferraz Néto, K. (2014). Análise gênica de comorbidades a partir da integração de dados epidemiológicos. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/95/95131/tde-29012015-150351/ ;

Chicago Manual of Style (16th Edition):

Ferraz Néto, Karla. “Análise gênica de comorbidades a partir da integração de dados epidemiológicos.” 2014. Masters Thesis, University of São Paulo. Accessed December 12, 2019. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-29012015-150351/ ;.

MLA Handbook (7th Edition):

Ferraz Néto, Karla. “Análise gênica de comorbidades a partir da integração de dados epidemiológicos.” 2014. Web. 12 Dec 2019.

Vancouver:

Ferraz Néto K. Análise gênica de comorbidades a partir da integração de dados epidemiológicos. [Internet] [Masters thesis]. University of São Paulo; 2014. [cited 2019 Dec 12]. Available from: http://www.teses.usp.br/teses/disponiveis/95/95131/tde-29012015-150351/ ;.

Council of Science Editors:

Ferraz Néto K. Análise gênica de comorbidades a partir da integração de dados epidemiológicos. [Masters Thesis]. University of São Paulo; 2014. Available from: http://www.teses.usp.br/teses/disponiveis/95/95131/tde-29012015-150351/ ;


Texas A&M University

18. Chin, See Loong. Incomplete gene structure prediction with almost 100% specificity.

Degree: 2004, Texas A&M University

 The goals of gene prediction using computational approaches are to determine gene location and the corresponding functionality of the coding region. A subset of gene(more)

Subjects/Keywords: Gene Structure Prediction; Dynamic Programming; Specificity

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APA (6th Edition):

Chin, S. L. (2004). Incomplete gene structure prediction with almost 100% specificity. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/258

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chin, See Loong. “Incomplete gene structure prediction with almost 100% specificity.” 2004. Thesis, Texas A&M University. Accessed December 12, 2019. http://hdl.handle.net/1969.1/258.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chin, See Loong. “Incomplete gene structure prediction with almost 100% specificity.” 2004. Web. 12 Dec 2019.

Vancouver:

Chin SL. Incomplete gene structure prediction with almost 100% specificity. [Internet] [Thesis]. Texas A&M University; 2004. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1969.1/258.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chin SL. Incomplete gene structure prediction with almost 100% specificity. [Thesis]. Texas A&M University; 2004. Available from: http://hdl.handle.net/1969.1/258

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Akron

19. Yedida, Venkata Rama Kumar Swamy. Protein Function Prediction Using Decision Tree Technique.

Degree: MS, Computer Science, 2008, University of Akron

 The human genome project and numerous other genome projects have produced a large and ever increasing amount of sequence data. One of the main research… (more)

Subjects/Keywords: Bioinformatics; protein function prediction; decision tree; data mining; gene ontology; sequence similairty

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yedida, V. R. K. S. (2008). Protein Function Prediction Using Decision Tree Technique. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1216313412

Chicago Manual of Style (16th Edition):

Yedida, Venkata Rama Kumar Swamy. “Protein Function Prediction Using Decision Tree Technique.” 2008. Masters Thesis, University of Akron. Accessed December 12, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1216313412.

MLA Handbook (7th Edition):

Yedida, Venkata Rama Kumar Swamy. “Protein Function Prediction Using Decision Tree Technique.” 2008. Web. 12 Dec 2019.

Vancouver:

Yedida VRKS. Protein Function Prediction Using Decision Tree Technique. [Internet] [Masters thesis]. University of Akron; 2008. [cited 2019 Dec 12]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1216313412.

Council of Science Editors:

Yedida VRKS. Protein Function Prediction Using Decision Tree Technique. [Masters Thesis]. University of Akron; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1216313412


Universidade do Minho

20. Pacheco, José Carlos Ribeiro. PGP: prokaryote gene prediction software .

Degree: 2013, Universidade do Minho

 A correta previsão e anotação de genes bacterianos é essencial para a aplicação da informação contida no ADN em muitos tópicos de pesquisa (bio)médica, como… (more)

Subjects/Keywords: Ab initio; Bactéria; Genoma; Homologia; Previsão de genes; Sequenciação; Genome; Homology; Gene prediction; Sequencing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pacheco, J. C. R. (2013). PGP: prokaryote gene prediction software . (Masters Thesis). Universidade do Minho. Retrieved from http://hdl.handle.net/1822/27894

Chicago Manual of Style (16th Edition):

Pacheco, José Carlos Ribeiro. “PGP: prokaryote gene prediction software .” 2013. Masters Thesis, Universidade do Minho. Accessed December 12, 2019. http://hdl.handle.net/1822/27894.

MLA Handbook (7th Edition):

Pacheco, José Carlos Ribeiro. “PGP: prokaryote gene prediction software .” 2013. Web. 12 Dec 2019.

Vancouver:

Pacheco JCR. PGP: prokaryote gene prediction software . [Internet] [Masters thesis]. Universidade do Minho; 2013. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1822/27894.

Council of Science Editors:

Pacheco JCR. PGP: prokaryote gene prediction software . [Masters Thesis]. Universidade do Minho; 2013. Available from: http://hdl.handle.net/1822/27894

21. Salvi, Francesca. Kinetic and Structural Studies on Flavin-dependent Enzymes involved in Glycine Betaine Biosynthesis and Propionate 3-nitronate Detoxification.

Degree: PhD, Chemistry, 2015, Georgia State University

  Flavin-dependent enzymes are characterized by an amazing chemical versatility and play important roles in different cellular pathways. The FAD-containing choline oxidase from Arthrobacter globiformis… (more)

Subjects/Keywords: Flavin; Choline oxidase; Nitronate monooxygenase; Propionate 3-nitronate; Choline dehydrogenase; Gene function prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Salvi, F. (2015). Kinetic and Structural Studies on Flavin-dependent Enzymes involved in Glycine Betaine Biosynthesis and Propionate 3-nitronate Detoxification. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/chemistry_diss/106

Chicago Manual of Style (16th Edition):

Salvi, Francesca. “Kinetic and Structural Studies on Flavin-dependent Enzymes involved in Glycine Betaine Biosynthesis and Propionate 3-nitronate Detoxification.” 2015. Doctoral Dissertation, Georgia State University. Accessed December 12, 2019. https://scholarworks.gsu.edu/chemistry_diss/106.

MLA Handbook (7th Edition):

Salvi, Francesca. “Kinetic and Structural Studies on Flavin-dependent Enzymes involved in Glycine Betaine Biosynthesis and Propionate 3-nitronate Detoxification.” 2015. Web. 12 Dec 2019.

Vancouver:

Salvi F. Kinetic and Structural Studies on Flavin-dependent Enzymes involved in Glycine Betaine Biosynthesis and Propionate 3-nitronate Detoxification. [Internet] [Doctoral dissertation]. Georgia State University; 2015. [cited 2019 Dec 12]. Available from: https://scholarworks.gsu.edu/chemistry_diss/106.

Council of Science Editors:

Salvi F. Kinetic and Structural Studies on Flavin-dependent Enzymes involved in Glycine Betaine Biosynthesis and Propionate 3-nitronate Detoxification. [Doctoral Dissertation]. Georgia State University; 2015. Available from: https://scholarworks.gsu.edu/chemistry_diss/106


University of South Carolina

22. Liu, Zhonghao. Machine Learning Based Disease Gene Identification and MHC Immune Protein-peptide Binding Prediction.

Degree: PhD, Computer Science and Engineering, 2018, University of South Carolina

  Machine learning and deep learning methods have been increasingly applied to solve challenging and important bioinformatics problems such as protein structure prediction, disease gene(more)

Subjects/Keywords: Computer Sciences; Machine Learning; Gene Identification; MHC Immune; Protein-peptide; Binding Prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Liu, Z. (2018). Machine Learning Based Disease Gene Identification and MHC Immune Protein-peptide Binding Prediction. (Doctoral Dissertation). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/5084

Chicago Manual of Style (16th Edition):

Liu, Zhonghao. “Machine Learning Based Disease Gene Identification and MHC Immune Protein-peptide Binding Prediction.” 2018. Doctoral Dissertation, University of South Carolina. Accessed December 12, 2019. https://scholarcommons.sc.edu/etd/5084.

MLA Handbook (7th Edition):

Liu, Zhonghao. “Machine Learning Based Disease Gene Identification and MHC Immune Protein-peptide Binding Prediction.” 2018. Web. 12 Dec 2019.

Vancouver:

Liu Z. Machine Learning Based Disease Gene Identification and MHC Immune Protein-peptide Binding Prediction. [Internet] [Doctoral dissertation]. University of South Carolina; 2018. [cited 2019 Dec 12]. Available from: https://scholarcommons.sc.edu/etd/5084.

Council of Science Editors:

Liu Z. Machine Learning Based Disease Gene Identification and MHC Immune Protein-peptide Binding Prediction. [Doctoral Dissertation]. University of South Carolina; 2018. Available from: https://scholarcommons.sc.edu/etd/5084


Wayne State University

23. Al aydie, Noor. Hierarchical multi-label classification for protein function prediction going beyond traditional approaches.

Degree: PhD, Computer Science, 2012, Wayne State University

  Hierarchical multi-label classification is a variant of traditional classification in which the instances can belong to several labels, that are in turn organized in… (more)

Subjects/Keywords: classification, gene function prediction, Hierarchical classification, integraion, multi-label, protein function classification; Bioinformatics; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Al aydie, N. (2012). Hierarchical multi-label classification for protein function prediction going beyond traditional approaches. (Doctoral Dissertation). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_dissertations/525

Chicago Manual of Style (16th Edition):

Al aydie, Noor. “Hierarchical multi-label classification for protein function prediction going beyond traditional approaches.” 2012. Doctoral Dissertation, Wayne State University. Accessed December 12, 2019. https://digitalcommons.wayne.edu/oa_dissertations/525.

MLA Handbook (7th Edition):

Al aydie, Noor. “Hierarchical multi-label classification for protein function prediction going beyond traditional approaches.” 2012. Web. 12 Dec 2019.

Vancouver:

Al aydie N. Hierarchical multi-label classification for protein function prediction going beyond traditional approaches. [Internet] [Doctoral dissertation]. Wayne State University; 2012. [cited 2019 Dec 12]. Available from: https://digitalcommons.wayne.edu/oa_dissertations/525.

Council of Science Editors:

Al aydie N. Hierarchical multi-label classification for protein function prediction going beyond traditional approaches. [Doctoral Dissertation]. Wayne State University; 2012. Available from: https://digitalcommons.wayne.edu/oa_dissertations/525


University of Minnesota

24. Pandey, Gaurav. Data mining techniques for enhancing protein function prediction.

Degree: PhD, Computer Science, 2010, University of Minnesota

 Proteins are the most essential and versatile macromolecules of life, and the knowledge of their functions is crucial for obtaining a basic understanding of the… (more)

Subjects/Keywords: Biclustering; Classification; Data mining; Gene expression data,; Protein function prediction; Protein interaction data; Computer Science

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APA (6th Edition):

Pandey, G. (2010). Data mining techniques for enhancing protein function prediction. (Doctoral Dissertation). University of Minnesota. Retrieved from http://purl.umn.edu/92467

Chicago Manual of Style (16th Edition):

Pandey, Gaurav. “Data mining techniques for enhancing protein function prediction.” 2010. Doctoral Dissertation, University of Minnesota. Accessed December 12, 2019. http://purl.umn.edu/92467.

MLA Handbook (7th Edition):

Pandey, Gaurav. “Data mining techniques for enhancing protein function prediction.” 2010. Web. 12 Dec 2019.

Vancouver:

Pandey G. Data mining techniques for enhancing protein function prediction. [Internet] [Doctoral dissertation]. University of Minnesota; 2010. [cited 2019 Dec 12]. Available from: http://purl.umn.edu/92467.

Council of Science Editors:

Pandey G. Data mining techniques for enhancing protein function prediction. [Doctoral Dissertation]. University of Minnesota; 2010. Available from: http://purl.umn.edu/92467


University of Guelph

25. Marhon, Sajid A. A New, Model-Independent, Spectrum-Based Gene Prediction Technique .

Degree: 2015, University of Guelph

 Detecting protein-coding regions is a fundamental step in genome analysis. This step is a precursor to analyzing protein sequences. Different techniques have been proposed for… (more)

Subjects/Keywords: Gene Prediction; Period-3 Spectrum; Protein Coding Regions; Digital Signal Processing; DNA Sequence Analysis

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APA (6th Edition):

Marhon, S. A. (2015). A New, Model-Independent, Spectrum-Based Gene Prediction Technique . (Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8767

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Marhon, Sajid A. “A New, Model-Independent, Spectrum-Based Gene Prediction Technique .” 2015. Thesis, University of Guelph. Accessed December 12, 2019. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8767.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Marhon, Sajid A. “A New, Model-Independent, Spectrum-Based Gene Prediction Technique .” 2015. Web. 12 Dec 2019.

Vancouver:

Marhon SA. A New, Model-Independent, Spectrum-Based Gene Prediction Technique . [Internet] [Thesis]. University of Guelph; 2015. [cited 2019 Dec 12]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8767.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Marhon SA. A New, Model-Independent, Spectrum-Based Gene Prediction Technique . [Thesis]. University of Guelph; 2015. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8767

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Saskatchewan

26. Luo, Ping 1988-. Identifying disease-associated genes based on artificial intelligence.

Degree: 2019, University of Saskatchewan

 Identifying disease-gene associations can help improve the understanding of disease mechanisms, which has a variety of applications, such as early diagnosis and drug development. Although… (more)

Subjects/Keywords: Disease gene prediction; artificial intelligence; machine learning; deep learning; complex network analysis

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APA (6th Edition):

Luo, P. 1. (2019). Identifying disease-associated genes based on artificial intelligence. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/12389

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Luo, Ping 1988-. “Identifying disease-associated genes based on artificial intelligence.” 2019. Thesis, University of Saskatchewan. Accessed December 12, 2019. http://hdl.handle.net/10388/12389.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Luo, Ping 1988-. “Identifying disease-associated genes based on artificial intelligence.” 2019. Web. 12 Dec 2019.

Vancouver:

Luo P1. Identifying disease-associated genes based on artificial intelligence. [Internet] [Thesis]. University of Saskatchewan; 2019. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/10388/12389.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Luo P1. Identifying disease-associated genes based on artificial intelligence. [Thesis]. University of Saskatchewan; 2019. Available from: http://hdl.handle.net/10388/12389

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Duke University

27. Lekprasert, Parawee. MicroRNA Target Prediction via Duplex Formation Features and Direct Binding Evidence .

Degree: 2012, Duke University

  MicroRNAs (miRNAs) are small RNAs that have important roles in post-transcriptional gene regulation in a wide range of species. This regulation is controlled by… (more)

Subjects/Keywords: Bioinformatics; AGO interaction; duplex energy; gene regulation; miRNA; miRNA target prediction; regulatory genomics

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APA (6th Edition):

Lekprasert, P. (2012). MicroRNA Target Prediction via Duplex Formation Features and Direct Binding Evidence . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/6175

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lekprasert, Parawee. “MicroRNA Target Prediction via Duplex Formation Features and Direct Binding Evidence .” 2012. Thesis, Duke University. Accessed December 12, 2019. http://hdl.handle.net/10161/6175.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lekprasert, Parawee. “MicroRNA Target Prediction via Duplex Formation Features and Direct Binding Evidence .” 2012. Web. 12 Dec 2019.

Vancouver:

Lekprasert P. MicroRNA Target Prediction via Duplex Formation Features and Direct Binding Evidence . [Internet] [Thesis]. Duke University; 2012. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/10161/6175.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lekprasert P. MicroRNA Target Prediction via Duplex Formation Features and Direct Binding Evidence . [Thesis]. Duke University; 2012. Available from: http://hdl.handle.net/10161/6175

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

28. CHANG XULING. GENETIC EPIDEMIOLOGICAL INVESTIGATIONS OF CORONARY ARTERY DISEASE AND ITS RISK FACTORS.

Degree: 2016, National University of Singapore

Subjects/Keywords: Coronary Artery Disease; risk prediction; gene-gene interaction; gene-environment interaction; association

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APA (6th Edition):

XULING, C. (2016). GENETIC EPIDEMIOLOGICAL INVESTIGATIONS OF CORONARY ARTERY DISEASE AND ITS RISK FACTORS. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/134920

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

XULING, CHANG. “GENETIC EPIDEMIOLOGICAL INVESTIGATIONS OF CORONARY ARTERY DISEASE AND ITS RISK FACTORS.” 2016. Thesis, National University of Singapore. Accessed December 12, 2019. http://scholarbank.nus.edu.sg/handle/10635/134920.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

XULING, CHANG. “GENETIC EPIDEMIOLOGICAL INVESTIGATIONS OF CORONARY ARTERY DISEASE AND ITS RISK FACTORS.” 2016. Web. 12 Dec 2019.

Vancouver:

XULING C. GENETIC EPIDEMIOLOGICAL INVESTIGATIONS OF CORONARY ARTERY DISEASE AND ITS RISK FACTORS. [Internet] [Thesis]. National University of Singapore; 2016. [cited 2019 Dec 12]. Available from: http://scholarbank.nus.edu.sg/handle/10635/134920.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

XULING C. GENETIC EPIDEMIOLOGICAL INVESTIGATIONS OF CORONARY ARTERY DISEASE AND ITS RISK FACTORS. [Thesis]. National University of Singapore; 2016. Available from: http://scholarbank.nus.edu.sg/handle/10635/134920

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. M. Notaro. HIERARCHICAL ENSEMBLE METHODS FOR ONTOLOGY-BASED PREDICTIONS IN COMPUTATIONAL BIOLOGY.

Degree: 2019, Università degli Studi di Milano

 L'annotazione standardizzata di entità biologiche, quali geni e proteine, ha fortemente promosso l'organizzazione dei concetti biologici in vocabolari controllati, cioè ontologie che consentono di indicizzare… (more)

Subjects/Keywords: Hierarchical Ensemble Methods; Hierarchical Multi-Label Classification; Human Phenotype Ontology; Gene Ontology; Gene-Abnormal Phenotype Association; Protein Function Prediction; Human Phenotype Ontology Term Prediction; Gene Ontology Term Prediction; Phenotype Gene Prioritization; Bioinformatics; Computational Biology; Machine Learning; Settore INF/01 - Informatica; Settore BIO/11 - Biologia Molecolare; Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni

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APA (6th Edition):

Notaro, M. (2019). HIERARCHICAL ENSEMBLE METHODS FOR ONTOLOGY-BASED PREDICTIONS IN COMPUTATIONAL BIOLOGY. (Thesis). Università degli Studi di Milano. Retrieved from http://hdl.handle.net/2434/606185

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Notaro, M.. “HIERARCHICAL ENSEMBLE METHODS FOR ONTOLOGY-BASED PREDICTIONS IN COMPUTATIONAL BIOLOGY.” 2019. Thesis, Università degli Studi di Milano. Accessed December 12, 2019. http://hdl.handle.net/2434/606185.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Notaro, M.. “HIERARCHICAL ENSEMBLE METHODS FOR ONTOLOGY-BASED PREDICTIONS IN COMPUTATIONAL BIOLOGY.” 2019. Web. 12 Dec 2019.

Vancouver:

Notaro M. HIERARCHICAL ENSEMBLE METHODS FOR ONTOLOGY-BASED PREDICTIONS IN COMPUTATIONAL BIOLOGY. [Internet] [Thesis]. Università degli Studi di Milano; 2019. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/2434/606185.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Notaro M. HIERARCHICAL ENSEMBLE METHODS FOR ONTOLOGY-BASED PREDICTIONS IN COMPUTATIONAL BIOLOGY. [Thesis]. Università degli Studi di Milano; 2019. Available from: http://hdl.handle.net/2434/606185

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

30. Kashiwabara, Andre Yoshiaki. MYOP: um arcabouço para predição de genes ab initio\".

Degree: Mestrado, Ciência da Computação, 2007, University of São Paulo

A demanda por abordagens eficientes para o problema de reconhecer a estrutura de cada gene numa sequência genômica motivou a implementação de um grande número… (more)

Subjects/Keywords: bioinformática; Bioinformatics; cadeia de Markov oculta generalizada.; gene prediction; generalized hidden Markov model; predição de genes

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kashiwabara, A. Y. (2007). MYOP: um arcabouço para predição de genes ab initio\". (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/45/45134/tde-25112009-151237/ ;

Chicago Manual of Style (16th Edition):

Kashiwabara, Andre Yoshiaki. “MYOP: um arcabouço para predição de genes ab initio\".” 2007. Masters Thesis, University of São Paulo. Accessed December 12, 2019. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-25112009-151237/ ;.

MLA Handbook (7th Edition):

Kashiwabara, Andre Yoshiaki. “MYOP: um arcabouço para predição de genes ab initio\".” 2007. Web. 12 Dec 2019.

Vancouver:

Kashiwabara AY. MYOP: um arcabouço para predição de genes ab initio\". [Internet] [Masters thesis]. University of São Paulo; 2007. [cited 2019 Dec 12]. Available from: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-25112009-151237/ ;.

Council of Science Editors:

Kashiwabara AY. MYOP: um arcabouço para predição de genes ab initio\". [Masters Thesis]. University of São Paulo; 2007. Available from: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-25112009-151237/ ;

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