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Processing Conservation Indicators With Open Source Tools: Lessons Learned From The Digital Observatory For Protected Areas, Lucy Bastin, Andrea Mandrici, Luca Battistella, Grégoire Dubois 2017 European Commission, Joint Research Centre (JRC), Directorate D: Sustainable Resources, Knowledge for Sustainable Development and Food Security, Via E. Fermi 2749, I-21027 Ispra (VA), Italy

Processing Conservation Indicators With Open Source Tools: Lessons Learned From The Digital Observatory For Protected Areas, Lucy Bastin, Andrea Mandrici, Luca Battistella, Grégoire Dubois

Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings

The European Commission has a commitment to open data and the support of open source software and standards. We present lessons learnt while populating and supporting the web and map services that underly the Joint Research Centre's Digital Observatory for Protected Areas. Challenges include: large datasets with highly complex geometries; topological inconsistencies, compounded by reprojection for equal-area calculations; multiple different representations of the same geographical entities, for example coastlines; licensing requirement to continuously update indicators to respond to monthly changes in the authoritative data. In order to compute and publish an array of indicators, we used a range of ...


A Combined Computational Strategy Of Sequence And Structural Analysis Predicts The Existence Of A Functional Eicosanoid Pathway In Drosophila Melanogaster, Michael Scarpati 2017 The Graduate Center, City University of New York

A Combined Computational Strategy Of Sequence And Structural Analysis Predicts The Existence Of A Functional Eicosanoid Pathway In Drosophila Melanogaster, Michael Scarpati

All Graduate Works by Year: Dissertations, Theses, and Capstone Projects

With increased understanding of their roles in signal transduction and metabolism, eicosanoids have emerged as important players in human health and disease. Mammalian prostanoids and related lipid mediators perform varied functions in different tissues and organs. Synthesized through the oxygenation of C20 polyunsaturated fatty acids, mammalian eicosanoids are both pro- and anti-inflammatory. The physiological contexts in which eicosanoid family members act at the cellular level are not well understood. In this study, we examined whether the genome of Drosophila melanogaster, a powerful model for innate immunity and inflammation, codes for the enzymes required for eicosanoid biosynthesis. We report the existence ...


Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor 2017 The Graduate Center, City University of New York

Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor

All Graduate Works by Year: Dissertations, Theses, and Capstone Projects

Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.

Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world ...


Prtad: A Database For Protein Residue Torsion Angle Distributions, Xiaoyong Sun, Di Wu, Robert L. Jernigan, Zhijun Wu 2017 Iowa State University

Prtad: A Database For Protein Residue Torsion Angle Distributions, Xiaoyong Sun, Di Wu, Robert L. Jernigan, Zhijun Wu

Robert Jernigan

PRTAD is a dedicated database and structural bioinformatics system for protein analysis and modelling. The database is developed to host and analyse the statistical data for protein residue level 'virtual' bond and torsion angles obtained from their distributions in databases of known protein structures such as in the PDB Data Bank. PRTAD is capable of generating, caching, and displaying the statistical distributions of the angles of various types. The collected information can be used to extract geometric restraints or define statistical potentials for protein structure determination. PRTAD is supported with a friendly designed web interface so that users can easily ...


Regulatory Rna: Session Introduction, Drena Dobbs, Steven E. Brenner, Vasant G. Honavar, Robert L. Jernigan, Alain Laederach, Quaid Morris 2017 Iowa State University

Regulatory Rna: Session Introduction, Drena Dobbs, Steven E. Brenner, Vasant G. Honavar, Robert L. Jernigan, Alain Laederach, Quaid Morris

Robert Jernigan

Advances in both experimental and computational approaches to genome-wide analysis of RNA transcripts have dramatically expanded our understanding of the ubiquitous and diverse roles of regulatory non-coding RNAs. This conference session includes presentations exploring computational approaches for detecting regulatory RNAs in RNA-Seq data, for analyzing in vivo CLIP data on RNA-protein interactions, and for predicting interfacial residues involved in RNA-protein recognition in RNA–protein complexes and interaction networks.


Elastic Network Models Capture The Motions Apparent Within Ensembles Of Rna Structures, Michael T. Zimmermann, Robert L. Jernigan 2017 Iowa State University

Elastic Network Models Capture The Motions Apparent Within Ensembles Of Rna Structures, Michael T. Zimmermann, Robert L. Jernigan

Robert Jernigan

The role of structure and dynamics in mechanisms for RNA becomes increasingly important. Computational approaches using simple dynamics models have been successful at predicting the motions of proteins and are often applied to ribonucleo-protein complexes but have not been thoroughly tested for well-packed nucleic acid structures. In order to characterize a true set of motions, we investigate the apparent motions from 16 ensembles of experimentally determined RNA structures. These indicate a relatively limited set of motions that are captured by a small set of principal components (PCs). These limited motions closely resemble the motions computed from low frequency normal modes ...


Prediction Of Rna Binding Sites In Proteins From Amino Acid Sequence, Michael Terribilini, Jae-Hyung Lee, Changhui Yan, Robert L. Jernigan, Vasant Honavar, Drena Dobbs 2017 Iowa State University

Prediction Of Rna Binding Sites In Proteins From Amino Acid Sequence, Michael Terribilini, Jae-Hyung Lee, Changhui Yan, Robert L. Jernigan, Vasant Honavar, Drena Dobbs

Robert Jernigan

RNA–protein interactions are vitally important in a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have developed a computational tool for predicting which amino acids of an RNA binding protein participate in RNA–protein interactions, using only the protein sequence as input. RNABindR was developed using machine learning on a validated nonredundant data set of interfaces from known RNA–protein complexes in the Protein Data Bank. It generates a classifier that captures primary sequence signals sufficient for predicting which amino acids in a given protein are located ...


Predicting Dna-Binding Sites Of Proteins From Amino Acid Sequence, Changhui Yan, Michael Terribilini, Feihong Wu, Robert L. Jernigan, Drena Dobbs, Vasant Honavar 2017 Utah State University

Predicting Dna-Binding Sites Of Proteins From Amino Acid Sequence, Changhui Yan, Michael Terribilini, Feihong Wu, Robert L. Jernigan, Drena Dobbs, Vasant Honavar

Robert Jernigan

Background

Understanding the molecular details of protein-DNA interactions is critical for deciphering the mechanisms of gene regulation. We present a machine learning approach for the identification of amino acid residues involved in protein-DNA interactions.

Results

We start with a Naïve Bayes classifier trained to predict whether a given amino acid residue is a DNA-binding residue based on its identity and the identities of its sequence neighbors. The input to the classifier consists of the identities of the target residue and 4 sequence neighbors on each side of the target residue. The classifier is trained and evaluated (using leave-one-out cross-validation) on ...


Identifying Interaction Sites In "Recalcitrant" Proteins: Predicted Protein And Rna Binding Sites In Rev Proteins Of Hiv-1 And Eiav Agree With Experimental Data, Michael Terribilini, Jae-Hyung Lee, Changhui Yan, Robert L. Jernigan, Susan Carpenter, Vasant Honavar, Drena Dobbs 2017 Iowa State University

Identifying Interaction Sites In "Recalcitrant" Proteins: Predicted Protein And Rna Binding Sites In Rev Proteins Of Hiv-1 And Eiav Agree With Experimental Data, Michael Terribilini, Jae-Hyung Lee, Changhui Yan, Robert L. Jernigan, Susan Carpenter, Vasant Honavar, Drena Dobbs

Robert Jernigan

Protein-protein and protein nucleic acid interactions are vitally important for a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have developed machine learning approaches for predicting which amino acids of a protein participate in its interactions with other proteins and/or nucleic acids, using only the protein sequence as input. In this paper, we describe an application of classifiers trained on datasets of well-characterized protein-protein and protein-RNA complexes for which experimental structures are available. We apply these classifiers to the problem of predicting protein and RNA binding sites ...


Rnabindr: A Server For Analyzing And Predicting Rna-Binding Sites In Proteins, Michael Terribilini, Jeffry D. Sander, Jae-Hyung Lee, Peter Zaback, Robert L. Jernigan, Vasant Honavar, Drena Dobbs 2017 Iowa State University

Rnabindr: A Server For Analyzing And Predicting Rna-Binding Sites In Proteins, Michael Terribilini, Jeffry D. Sander, Jae-Hyung Lee, Peter Zaback, Robert L. Jernigan, Vasant Honavar, Drena Dobbs

Robert Jernigan

Understanding interactions between proteins and RNA is key to deciphering the mechanisms of many important biological processes. Here we describe RNABindR, a web-based server that identifies and displays RNA-binding residues in known protein–RNA complexes and predicts RNA-binding residues in proteins of unknown structure. RNABindR uses a distance cutoff to identify which amino acids contact RNA in solved complex structures (from the Protein Data Bank) and provides a labeled amino acid sequence and a Jmol graphical viewer in which RNA-binding residues are displayed in the context of the three-dimensional structure. Alternatively, RNABindR can use a Naive Bayes classifier trained on ...


Predicting Binding Sites Of Hydrolase-Inhibitor Complexes By Combining Several Methods, Taner Z. Sen, Andrzej Kloczkowski, Robert L. Jernigan, Changhui Yan, Vasant Honovar, Kai-Ming Ho, Cai-Zhuang Wang, Yungok Ihm, Haibo Cao, Xun Gu, Drena Dobbs 2017 Iowa State University

Predicting Binding Sites Of Hydrolase-Inhibitor Complexes By Combining Several Methods, Taner Z. Sen, Andrzej Kloczkowski, Robert L. Jernigan, Changhui Yan, Vasant Honovar, Kai-Ming Ho, Cai-Zhuang Wang, Yungok Ihm, Haibo Cao, Xun Gu, Drena Dobbs

Robert Jernigan

Background

Protein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting protein pairs experimentally in order to decipher the networks of interacting, coordinated-in-action proteins. Identification of protein-protein interaction sites and detection of specific amino acids that contribute to the specificity and the strength of protein interactions is an important problem with broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks.

Results

In order to increase the power of predictive methods for protein-protein interaction sites, we have developed a consensus methodology ...


Characterization Of Protein–Protein Interfaces, Changhui Yan, Feihong Wu, Robert L. Jernigan, Drena Dobbs, Vasant Honavar 2017 Utah State University

Characterization Of Protein–Protein Interfaces, Changhui Yan, Feihong Wu, Robert L. Jernigan, Drena Dobbs, Vasant Honavar

Robert Jernigan

We analyze the characteristics of protein–protein interfaces using the largest datasets available from the Protein Data Bank (PDB). We start with a comparison of interfaces with protein cores and noninterface surfaces. The results show that interfaces differ from protein cores and non-interface surfaces in residue composition, sequence entropy, and secondary structure. Since interfaces, protein cores, and non-interface surfaces have different solvent accessibilities, it is important to investigate whether the observed differences are due to the differences in solvent accessibility or differences in functionality. We separate out the effect of solvent accessibility by comparing interfaces with a set of residues ...


Amelioration Of Prenatal Alcohol Effects By Environmental Enrichment In A Mouse Model Of Fasd, Aniruddho Chokroborty-Hoque 2017 The University of Western Ontario

Amelioration Of Prenatal Alcohol Effects By Environmental Enrichment In A Mouse Model Of Fasd, Aniruddho Chokroborty-Hoque

Electronic Thesis and Dissertation Repository

Maternal alcohol consumption during pregnancy results in a spectrum of behavioural and cognitive deficits collectively known as Fetal Alcohol Spectrum Disorders (FASD). Currently, little is know about if and how the external environment may modulate these deficits. I have used C57BL/6 mice to study this interaction between prenatal alcohol exposure and the postnatal environment. Alcohol exposure during synaptogenesis produces high levels of anxiety-like traits and decreased memory performance. Alcohol-exposed mice (and matched unexposed controls) were put in 'environmentally-enriched' conditions of voluntary exercise, physical activities and cognitive stimulation to ascertain the effects of a positive postnatal environment. The results show ...


The In-Feed Antibiotic Carbadox Induces Phage Gene Transcription In The Swine Gut Microbiome, Timothy A. Johnson, Torey Looft, Andrew J. Severin 2017 United States Department of Agriculture

The In-Feed Antibiotic Carbadox Induces Phage Gene Transcription In The Swine Gut Microbiome, Timothy A. Johnson, Torey Looft, Andrew J. Severin

Andrew Severin

Carbadox is a quinoxaline-di-N-oxide antibiotic fed to over 40% of young pigs in the United States that has been shown to induce phage DNA transduction in vitro; however, the effects of carbadox on swine microbiome functions are poorly understood. We investigated the in vivo longitudinal effects of carbadox on swine gut microbial gene expression (fecal metatranscriptome) and phage population dynamics (fecal dsDNA viromes). Microbial metagenome, transcriptome, and virome sequences were annotated for taxonomic inference and gene function by using FIGfam (isofunctional homolog sequences) and SEED subsystems databases. When the beta diversities of microbial FIGfam annotations were compared, the control and ...


Transcriptomic Responses To Environmental Temperature By Turtles With Temperature-Dependent And Genotypic Sex Determination Assessed By Rnaseq Inform The Genetic Architecture Of Embryonic Gonadal Development, Srihari Radhakrishnan, Robert A. Literman, Jennifer L. Neuwald, Andrew Severin, Nicole Valenzuela 2017 Iowa State University

Transcriptomic Responses To Environmental Temperature By Turtles With Temperature-Dependent And Genotypic Sex Determination Assessed By Rnaseq Inform The Genetic Architecture Of Embryonic Gonadal Development, Srihari Radhakrishnan, Robert A. Literman, Jennifer L. Neuwald, Andrew Severin, Nicole Valenzuela

Andrew Severin

Vertebrate sexual fate is decided primarily by the individual’s genotype (GSD), by the environmental temperature during development (TSD), or both. Turtles exhibit TSD and GSD, making them ideal to study the evolution of sex determination. Here we analyze temperature-specific gonadal transcriptomes (RNA-sequencing validated by qPCR) of painted turtles (Chrysemys picta TSD) before and during the thermosensitive period, and at equivalent stages in soft-shell turtles (Apalone spinifera—GSD), to test whether TSD’s and GSD’s transcriptional circuitry is identical but deployed differently between mechanisms. Our data show that most elements of the mammalian urogenital network are active during turtle ...


Unravelling Organelle Genome Transcription Using Publicly Available Rna-Sequencing Data, Matheus Sanita Lima 2017 The University of Western Ontario

Unravelling Organelle Genome Transcription Using Publicly Available Rna-Sequencing Data, Matheus Sanita Lima

Electronic Thesis and Dissertation Repository

The study of organelles helped forge theories of genome evolution because of their unconventional genomes and gene expression regimes. The organelle genomics field (~35 years old) has seen the development of next generation sequencing (NGS) techniques and the consequent skyrocketing of genomic and transcriptomic data. However, these data are being underused in the studies of organelle genome transcription. My thesis investigates how NGS has affected the field of organelle genomics at both the DNA and RNA levels. First, I demonstrate that although organelle genomes are being sequenced as never before, they are un-characterized as they are published mostly as “organelle ...


Accurate Cytogenetic Biodosimetry Through Automated Dicentric Chromosome Curation And Metaphase Cell Selection, Jin Liu, Yanxin Li, Ruth Wilkins, Canadian Nuclear Laboratories, Joan H. Knoll, Peter Rogan 2017 Western University

Accurate Cytogenetic Biodosimetry Through Automated Dicentric Chromosome Curation And Metaphase Cell Selection, Jin Liu, Yanxin Li, Ruth Wilkins, Canadian Nuclear Laboratories, Joan H. Knoll, Peter Rogan

Biochemistry Publications

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs ...


Machine Learning Based Protein Sequence To (Un)Structure Mapping And Interaction Prediction, Sumaiya Iqbal 2017 University of New Orleans, New Orleans

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 ...


The In-Feed Antibiotic Carbadox Induces Phage Gene Transcription In The Swine Gut Microbiome, Timothy A. Johnson, Torey Looft, Andrew J. Severin, Darrell O. Bayles, Daniel J. Nasko, K. Eric Wommack, Adina Howe, Heather K. Allen 2017 United States Department of Agriculture

The In-Feed Antibiotic Carbadox Induces Phage Gene Transcription In The Swine Gut Microbiome, Timothy A. Johnson, Torey Looft, Andrew J. Severin, Darrell O. Bayles, Daniel J. Nasko, K. Eric Wommack, Adina Howe, Heather K. Allen

Agricultural and Biosystems Engineering Publications

Carbadox is a quinoxaline-di-N-oxide antibiotic fed to over 40% of young pigs in the United States that has been shown to induce phage DNA transduction in vitro; however, the effects of carbadox on swine microbiome functions are poorly understood. We investigated the in vivo longitudinal effects of carbadox on swine gut microbial gene expression (fecal metatranscriptome) and phage population dynamics (fecal dsDNA viromes). Microbial metagenome, transcriptome, and virome sequences were annotated for taxonomic inference and gene function by using FIGfam (isofunctional homolog sequences) and SEED subsystems databases. When the beta diversities of microbial FIGfam annotations were compared, the ...


Vascular Endothelial Growth Factor A And Leptin Expression Associated With Ectopic Proliferation And Retinal Dysplasia In Zebrafish Optic Pathway Tumors, Laura E. Schultz, Staci L. Solin, Welsey A. Wierson, Janna M. Lovan, Judith Syrkin-Nikolau, Deborah E. Lincow, Andrew J. Severin, Donald S. Sakaguchi, Maura McGrail 2017 Iowa State University

Vascular Endothelial Growth Factor A And Leptin Expression Associated With Ectopic Proliferation And Retinal Dysplasia In Zebrafish Optic Pathway Tumors, Laura E. Schultz, Staci L. Solin, Welsey A. Wierson, Janna M. Lovan, Judith Syrkin-Nikolau, Deborah E. Lincow, Andrew J. Severin, Donald S. Sakaguchi, Maura Mcgrail

Genetics, Development and Cell Biology Publications

the central nervous system injury induces cellular reprogramming and progenitor proliferation, but the molecular mechanisms that limit regeneration and prevent tumorigenesis are not completely understood. We previously described a zebrafish optic pathway tumor model in which transgenic Tg(flk1:RFP)is18/+ adults develop nonmalignant retinal tumors. Key pathways driving injury-induced glial reprogramming and regeneration contributed to tumor formation. In this study, we examine a time course of proliferation and present new analyses of the Tg(flk1:RFP)is18/+ dysplastic retina and tumor transcriptomes. Retinal dysplasia was first detected in 3-month-old adults, but was not limited to a specific stem cell ...


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