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Articles 1 - 11 of 11
Full-Text Articles in Life Sciences
The Importance Of Physicochemical Characteristics And Nonlinear Classifiers In Determining Hiv-1 Protease Specificity, Timmy Manning, Paul Walsh
The Importance Of Physicochemical Characteristics And Nonlinear Classifiers In Determining Hiv-1 Protease Specificity, Timmy Manning, Paul Walsh
Department of Biological Sciences Publications
This paper reviews recent research relating to the application of bioinformatics approaches to determining HIV-1 protease specificity, outlines outstanding issues, and presents a new approach to addressing these issues. Leading machine learning theory for the problem currently suggests that the direct encoding of the physicochemical properties of the amino acid substrates is not required for optimal performance. A number of amino acid encoding approaches which incorporate potentially relevant physicochemical properties of the substrate are identified, and are evaluated using a nonlinear task decomposition based neuroevolution algorithm. The results are evaluated, and compared against a recent benchmark set on a nonlinear …
Obtaining Genomic Sequence Practice, Sarah O'Leary-Driscoll
Obtaining Genomic Sequence Practice, Sarah O'Leary-Driscoll
Introduction to NCBI
No abstract provided.
3: Genomics: Past & Future Bibliography, Sarah O'Leary-Driscoll
3: Genomics: Past & Future Bibliography, Sarah O'Leary-Driscoll
Genomics: Past & Future
No abstract provided.
Future Of Genomics: Presentations, Sarah O'Leary-Driscoll
Future Of Genomics: Presentations, Sarah O'Leary-Driscoll
Genomics: Past & Future
In his testimony to a House of Representatives sub-committee on health, director of the National Human Genome Research Institute, Francis S. Collins, said that the future of genomics had three main focal points:
"Genomics to Biology: The human genome sequence provides foundational information that now will allow development of a comprehensive catalog of all of the genome's components, determination of the function of all human genes, and deciphering of how genes and proteins work together in pathways and networks.
Genomics to Health: Completion of the human genome sequence offers a unique opportunity to understand the role of genetic factors in …
An Exploration Of The Phylogenetic Placement Of Recently Discovered Ultrasmall Archaeal Lineages, Jeffrey M. O'Brien
An Exploration Of The Phylogenetic Placement Of Recently Discovered Ultrasmall Archaeal Lineages, Jeffrey M. O'Brien
Honors Scholar Theses
In recent years, several new clades within the domain Achaea have been discovered. This is due in part to microbiological sampling of novel environments, and the increasing ability to detect and sequence uncultivable organisms through metagenomic analysis. These organisms share certain features, such as small cell size and streamlined genomes. Reduction in genome size can present difficulties to phylogenetic reconstruction programs. Since there is less genetic data to work with, these organisms often have missing genes in concatenated multiple sequence alignments. Evolutionary Biologists have not reached a consensus on the placement of these lineages in the archaeal evolutionary tree. There …
The Role Of Visualization And 3-D Printing In Biological Data Mining, Talia L. Weiss, Amanda Zieselman, Douglas P. Hill, Solomon G. Diamond, Li Shen, Andrew J. Saykin, Jason H. Moore
The Role Of Visualization And 3-D Printing In Biological Data Mining, Talia L. Weiss, Amanda Zieselman, Douglas P. Hill, Solomon G. Diamond, Li Shen, Andrew J. Saykin, Jason H. Moore
Dartmouth Scholarship
Background:
Biological data mining is a powerful tool that can provide a wealth of information about patterns of genetic and genomic biomarkers of health and disease. A potential disadvantage of data mining is volume and complexity of the results that can often be overwhelming. It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results. More specifically, we propose that 3-D printing has an important role to play as a visualization technology in biological data mining. We provide here a brief review of 3-D printing along with a case study to …
Draft Genome Sequences Of Six Different Staphylococcus Epidermidis Clones, Isolated Individually From Preterm Neonates Presenting With Sepsis At Edinburgh's Royal Infirmary, Paul Walsh, M. Bekaert, J. Carroll, T. Manning, B. Kelly, A. O'Driscoll, X. Lu, C. Smith, P. Dickinson, K. Templeton, P. Ghazal, Roy D. Sleator
Draft Genome Sequences Of Six Different Staphylococcus Epidermidis Clones, Isolated Individually From Preterm Neonates Presenting With Sepsis At Edinburgh's Royal Infirmary, Paul Walsh, M. Bekaert, J. Carroll, T. Manning, B. Kelly, A. O'Driscoll, X. Lu, C. Smith, P. Dickinson, K. Templeton, P. Ghazal, Roy D. Sleator
Department of Biological Sciences Publications
Herein, we report the draft genome sequences of six individual Staphylococcus epidermidis clones, cultivated from blood taken from different preterm neonatal sepsis patients at the Royal Infirmary, Edinburgh, Scotland, United Kingdom.
Evaluation Of Some Statistical Methods For The Identification Of Differentially Expressed Genes, Andrew L. Haddon
Evaluation Of Some Statistical Methods For The Identification Of Differentially Expressed Genes, Andrew L. Haddon
FIU Electronic Theses and Dissertations
Microarray platforms have been around for many years and while there is a rise of new technologies in laboratories, microarrays are still prevalent. When it comes to the analysis of microarray data to identify differentially expressed (DE) genes, many methods have been proposed and modified for improvement. However, the most popular methods such as Significance Analysis of Microarrays (SAM), samroc, fold change, and rank product are far from perfect. When it comes down to choosing which method is most powerful, it comes down to the characteristics of the sample and distribution of the gene expressions. The most practiced method is …
Introduction To Gene Enrichment Analysis Tools, Rolando Garcia-Milian
Introduction To Gene Enrichment Analysis Tools, Rolando Garcia-Milian
Rolando Garcia-Milian
Bioinformatics enrichment tools play an important role in identifying, annotating, and functionally analyzing large list of genes generated by high-throughput technologies (e.g. microarrary, RNA-seq, ChIP-chip). This workshop will provide an overview of the principle, type of enrichments, and the infrastructure of enrichment tools. By using concrete examples, it will also introduce some of the most popular tools for gene enrichment analysis such as DAVID, GSEA, and WebGestalt.
Establishment Of Biotrophy By The Maize Anthracnose Pathogen Colletotrichum Graminicola: Use Of Bioinformatics And Transcriptomics To Address The Potential Roles Of Secretion, Stress Response, And Secreted Proteins, Ester Alvarenga Santos Buiate
Establishment Of Biotrophy By The Maize Anthracnose Pathogen Colletotrichum Graminicola: Use Of Bioinformatics And Transcriptomics To Address The Potential Roles Of Secretion, Stress Response, And Secreted Proteins, Ester Alvarenga Santos Buiate
Theses and Dissertations--Plant Pathology
Colletotrichum graminicola is a hemibiotrophic pathogen of maize that causes anthracnose leaf and stalk rot diseases. The pathogen penetrates the host and initially establishes an intracellular biotrophic infection, in which the hyphae are separated from the living host cell by a membrane that is elaborated by the host, apparently in response to pathogen signals. A nonpathogenic mutant (MT) of C. graminicola was generated that germinates and penetrates the host normally, but is incapable of establishing a normal biotrophic infection. The mutated gene is Cpr1, conserved in eukaryotes and predicted to encode a component of the signal peptidase complex. How …
A Penalized Robust Semiparametric Approach For Gene-Environment Interactions, Shuangge Ma
A Penalized Robust Semiparametric Approach For Gene-Environment Interactions, Shuangge Ma
Shuangge Ma
In genetic and genomic studies, gene-environment (G*E) interactions have important implications. Some of the existing G$\times$E interaction methods are limited by analyzing a small number of G factors at a time, by assuming linear effects of E factors, by assuming no data contamination, and by adopting ineffective selection techniques. In this study, we propose a new approach for identifying important G*E interactions. It jointly models the effects of all E and G factors and their interactions. A partially linear varying coefficient model (PLVCM) is adopted to accommodate possible nonlinear effects of E factors. A rank-based loss function is used to …