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Full-Text Articles in Computational Biology

Punctuated Evolution Within A Eurythermic Genus (Mesenchytraeus) Of Segmented Worms: Genetic Modification Of The Glacier Ice Worm F1f0 Atp Synthase, Shirley A. Lang Dec 2016

Punctuated Evolution Within A Eurythermic Genus (Mesenchytraeus) Of Segmented Worms: Genetic Modification Of The Glacier Ice Worm F1f0 Atp Synthase, Shirley A. Lang

Graduate School of Biomedical Sciences Theses and Dissertations

Segmented worms (Annelida) are among the most successful animal inhabitants of extreme environments worldwide. An unusual group of Mesenchytraeus worms endemic to the Pacific Northwest of North America occupy geographically proximal ecozones ranging from low elevation temperate rainforests to high altitude glaciers. Along this altitudinal transect, Mesenchytraeus representatives from disparate habitat types were collected and subjected to deep mitochondrial and nuclear phylogenetic analyses. Evidence presented here employing modern bioinformatic analyses (i.e., maximum likelihood, Bayesian inference, multi-species coalescent) supports a Mesenchytraeus “explosion” in the upper Miocene (5-10 million years ago) that gave rise to ice, snow and terrestrial worms, derived from …


Development Of An In Silico Kir Genotyping Algorithm And Its Application To Population And Cancer Immunogenetic Analyses, Howard Rosoff Aug 2016

Development Of An In Silico Kir Genotyping Algorithm And Its Application To Population And Cancer Immunogenetic Analyses, Howard Rosoff

Dissertations & Theses (Open Access)

Gene content determination and variant calling in the complex KIR genomic region are useful for immune system function analysis, pathogenesis and disease risk factor elucidation, immunotherapy development, evolutionary investigations, and human migration modeling. Sequence-specific oligonucleotide and sequence-specific primer PCR methods are the de facto standards for KIR presence/absence identification, but the current platforms are unsuitable for SNP calling, impractical for KIR typing large cohorts of DNA samples, and inapplicable for typing repositories in which sequence data, but not cells or cell analytes, are available. Alternative typing methods, such as in silico sequence-based typing, can address the problems associated with amplicon-based …


Ten Simple Rules For Taking Advantage Of Git And Github, Yasset Perez-Riverol, Laurent Gatto, Rui Wang, Timo Sachsenberg, Julian Uszkoreit, Felipe Da Veiga Leprevost, Christian Fufezan, Tobias Ternent, Stephen J. Eglen, Daniel S. Katz, Tom J. Pollard, Alexander Konovalov, Robert M. Flight, Kai Blin, Juan Antonio Vizcaíno Jul 2016

Ten Simple Rules For Taking Advantage Of Git And Github, Yasset Perez-Riverol, Laurent Gatto, Rui Wang, Timo Sachsenberg, Julian Uszkoreit, Felipe Da Veiga Leprevost, Christian Fufezan, Tobias Ternent, Stephen J. Eglen, Daniel S. Katz, Tom J. Pollard, Alexander Konovalov, Robert M. Flight, Kai Blin, Juan Antonio Vizcaíno

Molecular and Cellular Biochemistry Faculty Publications

No abstract provided.


Computational Identification Of Terpene Synthase Genes And Their Evolutionary Analysis, Qidong Jia May 2016

Computational Identification Of Terpene Synthase Genes And Their Evolutionary Analysis, Qidong Jia

Doctoral Dissertations

Terpenoids, the largest and most structurally and functionally diverse class of natural compounds on earth, are mostly synthesized by plants to be involved in various plant environment interactions. Some terpenoids are classified as primary metabolites essential for plant growth and development. Terpene synthases (TPSs), the key enzymes for terpenoid biosynthesis, are the major determinant of the tremendous diversity of terpenoid carbon skeletons. The TPS genes represent a mid-size family of about 30-100 functional genes in almost all major sequenced plant genomes. TPSs are also found in fungi and bacteria, but microbial TPS genes share low levels of sequence similarity and …


Fastpop: A Rapid Principal Component Derived Method To Infer Intercontinental Ancestry Using Genetic Data, Yafang Li, Jinyoung Byun, Guoshuai Cai, Xiangjun Xiao, Younghun Han, Olivier Cornelis, James E. Dinulos, Joe Dennis, Douglas Easton, Ivan Gorlov, Michael F. Seldin, Christopher I. Amos Mar 2016

Fastpop: A Rapid Principal Component Derived Method To Infer Intercontinental Ancestry Using Genetic Data, Yafang Li, Jinyoung Byun, Guoshuai Cai, Xiangjun Xiao, Younghun Han, Olivier Cornelis, James E. Dinulos, Joe Dennis, Douglas Easton, Ivan Gorlov, Michael F. Seldin, Christopher I. Amos

Dartmouth Scholarship

Identifying subpopulations within a study and inferring intercontinental ancestry of the samples are important steps in genome wide association studies. Two software packages are widely used in analysis of substructure: Structure and Eigenstrat. Structure assigns each individual to a population by using a Bayesian method with multiple tuning parameters. It requires considerable computational time when dealing with thousands of samples and lacks the ability to create scores that could be used as covariates. Eigenstrat uses a principal component analysis method to model all sources of sampling variation. However, it does not readily provide information directly relevant to ancestral origin; the …


Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang Feb 2016

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …


A Pipeline For Creation Of Genome-Scale Metabolic Reconstructions, Shaun W. Norris Jan 2016

A Pipeline For Creation Of Genome-Scale Metabolic Reconstructions, Shaun W. Norris

Theses and Dissertations

The decreasing costs of next generation sequencing technologies and the increasing speeds at which they work have lead to an abundance of 'omic datasets. The need for tools and methods to analyze, annotate, and model these datasets to better understand biological systems is growing. Here we present a novel software pipeline to reconstruct the metabolic model of an organism in silico starting from its genome sequence and a novel compilation of biological databases to better serve the generation of metabolic models. We validate these methods using five Gardnerella vaginalis strains and compare the gene annotation results to NCBI and the …