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Articles 1 - 8 of 8
Full-Text Articles in Computational Biology
A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer
A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer
Konstantin Läufer
RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …
A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer
A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer
Catherine Putonti
RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …
Machine Learning Based Protein Sequence To (Un)Structure Mapping And Interaction Prediction, Sumaiya Iqbal
Machine Learning Based Protein Sequence To (Un)Structure Mapping And Interaction Prediction, Sumaiya Iqbal
University of New Orleans Theses and Dissertations
Proteins are the fundamental macromolecules within a cell that carry out most of the biological functions. The computational study of protein structure and its functions, using machine learning and data analytics, is elemental in advancing the life-science research due to the fast-growing biological data and the extensive complexities involved in their analyses towards discovering meaningful insights. Mapping of protein’s primary sequence is not only limited to its structure, we extend that to its disordered component known as Intrinsically Disordered Proteins or Regions in proteins (IDPs/IDRs), and hence the involved dynamics, which help us explain complex interaction within a cell that …
Annotation And Identification Of Several Glycerolipid Metabolic Related Ortholog Genes; Mrub_0437, Mrub_1813 And Mrub_2759 In The Organism Meithermus Ruber And Their Predicted Respective Orthologs B3926, B4042 And Bo514 Found In E.Coli., Abdul Rahman Abdul Kader, Dr. Lori R. Scott
Annotation And Identification Of Several Glycerolipid Metabolic Related Ortholog Genes; Mrub_0437, Mrub_1813 And Mrub_2759 In The Organism Meithermus Ruber And Their Predicted Respective Orthologs B3926, B4042 And Bo514 Found In E.Coli., Abdul Rahman Abdul Kader, Dr. Lori R. Scott
Meiothermus ruber Genome Analysis Project
We predict Mrub_0437 encodes the enzyme glycerol kinase (DNA coordinates [417621..419183), which is an intermediary step of the glycerolipid metabolic pathway (KEGG map00561), It catalyzes the conversion of glycerol to sn-Glycerol-3-phosphate. The E. coli K12 MG1655 ortholog is predicted to be b3926.
We predict Mrub_1813 encodes the enzyme diacylglycerol kinase (DNA coordinates [1864659..1865063), which is an intermediary step of the glycerolipid metabolic pathway (KEGG map00561), It catalyzes the conversion of 1,2-diacyl-sn-glycerol to 1,2-diacyl-sn-glycerol 3-phosphate. The E. coli K12 MG1655 ortholog is predicted to be b4042.
We predict Mrub_2759 encodes the enzyme glycerol kinase (DNA coordinates [2799712..2800665), which is an intermediary …
Identification Of Novel Sleep Related Genes From Large Scale Phenotyping Experiments In Mice, Shreyas Joshi
Identification Of Novel Sleep Related Genes From Large Scale Phenotyping Experiments In Mice, Shreyas Joshi
Theses and Dissertations--Biology
Humans spend a third of their lives sleeping but very little is known about the physiological and genetic mechanisms controlling sleep. Increased data from sleep phenotyping studies in mouse and other species, genetic crosses, and gene expression databases can all help improve our understanding of the process. Here, we present analysis of our own sleep data from the large-scale phenotyping program at The Jackson Laboratory (JAX), to identify the best gene candidates and phenotype predictors for influencing sleep traits.
The original knockout mouse project (KOMP) was a worldwide collaborative effort to produce embryonic stem (ES) cell lines with one of …
Network Analytics For The Mirna Regulome And Mirna-Disease Interactions, Joseph Jayakar Nalluri
Network Analytics For The Mirna Regulome And Mirna-Disease Interactions, Joseph Jayakar Nalluri
Theses and Dissertations
miRNAs are non-coding RNAs of approx. 22 nucleotides in length that inhibit gene expression at the post-transcriptional level. By virtue of this gene regulation mechanism, miRNAs play a critical role in several biological processes and patho-physiological conditions, including cancers. miRNA behavior is a result of a multi-level complex interaction network involving miRNA-mRNA, TF-miRNA-gene, and miRNA-chemical interactions; hence the precise patterns through which a miRNA regulates a certain disease(s) are still elusive. Herein, I have developed an integrative genomics methods/pipeline to (i) build a miRNA regulomics and data analytics repository, (ii) create/model these interactions into networks and use optimization techniques, motif …
Genomics Rna-Seq Analysis Part 2_ Kallisto Indexing And Quantification (Updated 11/17), Ray A. Enke, Melika Rahmani-Mofrad
Genomics Rna-Seq Analysis Part 2_ Kallisto Indexing And Quantification (Updated 11/17), Ray A. Enke, Melika Rahmani-Mofrad
Ray Enke Ph.D.
Genomics Rna-Seq Analysis Part 3-Sleuth Data Visualization (Updated 11/17), Ray A. Enke, Scott Schumacker
Genomics Rna-Seq Analysis Part 3-Sleuth Data Visualization (Updated 11/17), Ray A. Enke, Scott Schumacker
Ray Enke Ph.D.