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You searched for +publisher:"Rutgers University" +contributor:("Chen, Kevin"). Showing records 1 – 11 of 11 total matches.

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Rutgers University

1. Calviño Torterolo, Martĺn. Comparative genomics of the stem transcriptome from grain and sweet sorghum.

Degree: PhD, Plant Biology, 2014, Rutgers University

The current dissertation relates to comparative genomics of grain and sweet sorghum, in particular, to their stem’s transcriptome at the time of flowering, when soluble… (more)

Subjects/Keywords: Grain – Genome mapping; Sorghum – Genome mapping; Botanical chemistry

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APA (6th Edition):

Calviño Torterolo, M. (2014). Comparative genomics of the stem transcriptome from grain and sweet sorghum. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45214/

Chicago Manual of Style (16th Edition):

Calviño Torterolo, Martĺn. “Comparative genomics of the stem transcriptome from grain and sweet sorghum.” 2014. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45214/.

MLA Handbook (7th Edition):

Calviño Torterolo, Martĺn. “Comparative genomics of the stem transcriptome from grain and sweet sorghum.” 2014. Web. 26 Oct 2020.

Vancouver:

Calviño Torterolo M. Comparative genomics of the stem transcriptome from grain and sweet sorghum. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45214/.

Council of Science Editors:

Calviño Torterolo M. Comparative genomics of the stem transcriptome from grain and sweet sorghum. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45214/


Rutgers University

2. Diao, Liyang, 1986-. Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery.

Degree: PhD, Computational Biology and Molecular Biophysics, 2014, Rutgers University

If sheer number of papers published is indicative of anything, it suggests that the age of genome-wide association studies, or GWAS, is here to stay.… (more)

Subjects/Keywords: Linear models (Statistics); Genomes – Analysis

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APA (6th Edition):

Diao, Liyang, 1. (2014). Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45229/

Chicago Manual of Style (16th Edition):

Diao, Liyang, 1986-. “Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery.” 2014. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45229/.

MLA Handbook (7th Edition):

Diao, Liyang, 1986-. “Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery.” 2014. Web. 26 Oct 2020.

Vancouver:

Diao, Liyang 1. Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45229/.

Council of Science Editors:

Diao, Liyang 1. Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45229/


Rutgers University

3. Khan, Faisal M., 1981-. Semi-supervised transductive regression for survival analysis in medical prognostics.

Degree: PhD, Computer Science, 2016, Rutgers University

The central challenge in predictive modeling for survival analysis in medical prognostics is the management of censored observations in the data. While time-to-event predictions can… (more)

Subjects/Keywords: Survival analysis (Biometry)

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APA (6th Edition):

Khan, Faisal M., 1. (2016). Semi-supervised transductive regression for survival analysis in medical prognostics. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51331/

Chicago Manual of Style (16th Edition):

Khan, Faisal M., 1981-. “Semi-supervised transductive regression for survival analysis in medical prognostics.” 2016. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/51331/.

MLA Handbook (7th Edition):

Khan, Faisal M., 1981-. “Semi-supervised transductive regression for survival analysis in medical prognostics.” 2016. Web. 26 Oct 2020.

Vancouver:

Khan, Faisal M. 1. Semi-supervised transductive regression for survival analysis in medical prognostics. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51331/.

Council of Science Editors:

Khan, Faisal M. 1. Semi-supervised transductive regression for survival analysis in medical prognostics. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51331/


Rutgers University

4. Shanku, Alexander G., 1979-. Insights Into evolution and adaptation using computational methods and next generation sequencing.

Degree: PhD, Computational Biology and Molecular Biophysics, 2016, Rutgers University

 Historically, much of the research in evolutionary biology and population genetics has involved analysis at the level of either a single locus or a few… (more)

Subjects/Keywords: Evolution (Biology) – Mathematical models; Genomes – Analysis

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APA (6th Edition):

Shanku, Alexander G., 1. (2016). Insights Into evolution and adaptation using computational methods and next generation sequencing. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/50176/

Chicago Manual of Style (16th Edition):

Shanku, Alexander G., 1979-. “Insights Into evolution and adaptation using computational methods and next generation sequencing.” 2016. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/50176/.

MLA Handbook (7th Edition):

Shanku, Alexander G., 1979-. “Insights Into evolution and adaptation using computational methods and next generation sequencing.” 2016. Web. 26 Oct 2020.

Vancouver:

Shanku, Alexander G. 1. Insights Into evolution and adaptation using computational methods and next generation sequencing. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/50176/.

Council of Science Editors:

Shanku, Alexander G. 1. Insights Into evolution and adaptation using computational methods and next generation sequencing. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/50176/


Rutgers University

5. Mahmud, Md Pavel, 1981-. Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing.

Degree: PhD, Computer Science, 2014, Rutgers University

Since the genomics era has started in the ’70s, microarray technologies have been extensively used for biological applications such as gene expression profiling, copy number… (more)

Subjects/Keywords: Genomes – Analysis; Markov processes – Mathematical models; Bayesian statistical decision theory

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APA (6th Edition):

Mahmud, Md Pavel, 1. (2014). Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45336/

Chicago Manual of Style (16th Edition):

Mahmud, Md Pavel, 1981-. “Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing.” 2014. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45336/.

MLA Handbook (7th Edition):

Mahmud, Md Pavel, 1981-. “Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing.” 2014. Web. 26 Oct 2020.

Vancouver:

Mahmud, Md Pavel 1. Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45336/.

Council of Science Editors:

Mahmud, Md Pavel 1. Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45336/


Rutgers University

6. Roy, Rajat Shuvro, 1983-. Improving genome assembly by identifying reliable sequencing data.

Degree: PhD, Computer Science, 2014, Rutgers University

De novo Genome assembly and k-mer frequency counting are two of the classical prob- lems of Bioinformatics. k-mer counting helps to identify genomic k-mers from… (more)

Subjects/Keywords: Genomes – Analysis; Gene amplification

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APA (6th Edition):

Roy, Rajat Shuvro, 1. (2014). Improving genome assembly by identifying reliable sequencing data. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45449/

Chicago Manual of Style (16th Edition):

Roy, Rajat Shuvro, 1983-. “Improving genome assembly by identifying reliable sequencing data.” 2014. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45449/.

MLA Handbook (7th Edition):

Roy, Rajat Shuvro, 1983-. “Improving genome assembly by identifying reliable sequencing data.” 2014. Web. 26 Oct 2020.

Vancouver:

Roy, Rajat Shuvro 1. Improving genome assembly by identifying reliable sequencing data. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45449/.

Council of Science Editors:

Roy, Rajat Shuvro 1. Improving genome assembly by identifying reliable sequencing data. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45449/


Rutgers University

7. Manhart, Michael. Biophysics and stochastic processes in molecular evolution.

Degree: PhD, Physics and Astronomy, 2014, Rutgers University

Evolution is the defining feature of living matter. It occurs most fundamentally on the scale of biomolecules such as DNA and proteins, which carry out… (more)

Subjects/Keywords: Molecular evolution; Evolution (Biology); Protein folding

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APA (6th Edition):

Manhart, M. (2014). Biophysics and stochastic processes in molecular evolution. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45338/

Chicago Manual of Style (16th Edition):

Manhart, Michael. “Biophysics and stochastic processes in molecular evolution.” 2014. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45338/.

MLA Handbook (7th Edition):

Manhart, Michael. “Biophysics and stochastic processes in molecular evolution.” 2014. Web. 26 Oct 2020.

Vancouver:

Manhart M. Biophysics and stochastic processes in molecular evolution. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45338/.

Council of Science Editors:

Manhart M. Biophysics and stochastic processes in molecular evolution. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45338/

8. Gould, David William, 1986-. A research summary 1) RNA binding proteins, 2) Selective constraint on copy number variation in human PIWI-interacting RNA loci.

Degree: MS, Computational Biology and Molecular Biophysics, 2013, Rutgers University

 The overall aim of my research dealt with the understanding of regulatory elements in various systems (most important, in humans) through two research projects 1)… (more)

Subjects/Keywords: RNA-protein interactions; Genetic regulation

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APA (6th Edition):

Gould, David William, 1. (2013). A research summary 1) RNA binding proteins, 2) Selective constraint on copy number variation in human PIWI-interacting RNA loci. (Masters Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068863

Chicago Manual of Style (16th Edition):

Gould, David William, 1986-. “A research summary 1) RNA binding proteins, 2) Selective constraint on copy number variation in human PIWI-interacting RNA loci.” 2013. Masters Thesis, Rutgers University. Accessed October 26, 2020. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068863.

MLA Handbook (7th Edition):

Gould, David William, 1986-. “A research summary 1) RNA binding proteins, 2) Selective constraint on copy number variation in human PIWI-interacting RNA loci.” 2013. Web. 26 Oct 2020.

Vancouver:

Gould, David William 1. A research summary 1) RNA binding proteins, 2) Selective constraint on copy number variation in human PIWI-interacting RNA loci. [Internet] [Masters thesis]. Rutgers University; 2013. [cited 2020 Oct 26]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068863.

Council of Science Editors:

Gould, David William 1. A research summary 1) RNA binding proteins, 2) Selective constraint on copy number variation in human PIWI-interacting RNA loci. [Masters Thesis]. Rutgers University; 2013. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068863


Rutgers University

9. White, Amelia, 1977-. Automated and quantitative phenotyping of C. elegans genetic screens from high-throughput image data.

Degree: Computational Biology and Molecular Biophysics, 2013, Rutgers University

Subjects/Keywords: Computational biology; Diagnostic imaging; Caenorhabditis elegans – Research

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APA (6th Edition):

White, Amelia, 1. (2013). Automated and quantitative phenotyping of C. elegans genetic screens from high-throughput image data. (Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/41948/

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):

White, Amelia, 1977-. “Automated and quantitative phenotyping of C. elegans genetic screens from high-throughput image data.” 2013. Thesis, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/41948/.

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

MLA Handbook (7th Edition):

White, Amelia, 1977-. “Automated and quantitative phenotyping of C. elegans genetic screens from high-throughput image data.” 2013. Web. 26 Oct 2020.

Vancouver:

White, Amelia 1. Automated and quantitative phenotyping of C. elegans genetic screens from high-throughput image data. [Internet] [Thesis]. Rutgers University; 2013. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/41948/.

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

Council of Science Editors:

White, Amelia 1. Automated and quantitative phenotyping of C. elegans genetic screens from high-throughput image data. [Thesis]. Rutgers University; 2013. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/41948/

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


Rutgers University

10. Sasson, Ariella Syma, 1978-. From millions to one: theoretical and concrete approaches to De Novo assembly using short read DNA sequences.

Degree: PhD, Computational Biology and Molecular Biophysics, 2010, Rutgers University

One of the most significant advances in biology has been the ability to sequence the DNA of organisms. Even in the shadow of the completion… (more)

Subjects/Keywords: DNA – Research – Technique

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APA (6th Edition):

Sasson, Ariella Syma, 1. (2010). From millions to one: theoretical and concrete approaches to De Novo assembly using short read DNA sequences. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056766

Chicago Manual of Style (16th Edition):

Sasson, Ariella Syma, 1978-. “From millions to one: theoretical and concrete approaches to De Novo assembly using short read DNA sequences.” 2010. Doctoral Dissertation, Rutgers University. Accessed October 26, 2020. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056766.

MLA Handbook (7th Edition):

Sasson, Ariella Syma, 1978-. “From millions to one: theoretical and concrete approaches to De Novo assembly using short read DNA sequences.” 2010. Web. 26 Oct 2020.

Vancouver:

Sasson, Ariella Syma 1. From millions to one: theoretical and concrete approaches to De Novo assembly using short read DNA sequences. [Internet] [Doctoral dissertation]. Rutgers University; 2010. [cited 2020 Oct 26]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056766.

Council of Science Editors:

Sasson, Ariella Syma 1. From millions to one: theoretical and concrete approaches to De Novo assembly using short read DNA sequences. [Doctoral Dissertation]. Rutgers University; 2010. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056766


Rutgers University

11. Tsitron, Julia, 1976-. Computational analysis of olfaction and artificial nose technologies.

Degree: Computational Biology and Molecular Biophysics, 2013, Rutgers University

Subjects/Keywords: Olfactory sensors; Bayesian statistical decision theory

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APA (6th Edition):

Tsitron, Julia, 1. (2013). Computational analysis of olfaction and artificial nose technologies. (Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/41937/

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):

Tsitron, Julia, 1976-. “Computational analysis of olfaction and artificial nose technologies.” 2013. Thesis, Rutgers University. Accessed October 26, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/41937/.

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

MLA Handbook (7th Edition):

Tsitron, Julia, 1976-. “Computational analysis of olfaction and artificial nose technologies.” 2013. Web. 26 Oct 2020.

Vancouver:

Tsitron, Julia 1. Computational analysis of olfaction and artificial nose technologies. [Internet] [Thesis]. Rutgers University; 2013. [cited 2020 Oct 26]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/41937/.

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

Council of Science Editors:

Tsitron, Julia 1. Computational analysis of olfaction and artificial nose technologies. [Thesis]. Rutgers University; 2013. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/41937/

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

.