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IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Feng Cui Kriti Mukhopadhyay Won-Bin Young Robert L. Jernigan Zhijun Wu Program on Bioinformatics and Computational Biology Department of Mathematics USA University Research Park Ames IA USA Department of Biochemistry Biophysics and Molecular Biology Iowa State University USA Program on Bioinformatics and Computational Biology USA

computational simulations of the conversion from the normal cellular prion (PrP c ) to the scrapie prion (PrP Sc ) are usually based on the structures determined by NMR because of the difficulties in crystallizing prion protein. Due to insufficient experimental restraints, a biologically critical loop region in PrP c (residues 167-171), which is a potential binding site for Protein X, is under-determined in most mammalian species. Here, we show that by adding information about distance constraints derived from a database of high-resolution protein structures, this under-determined loop as well as other secondary structural elements of the E200K variant of human prion protein (hPrP c ), a disease-related isoform, can be refined into more realistic structures in the structural ensemble with improved quality and increased accuracy. In particular, the ensemble becomes more compact after the refinement and the percentage of residues in the most favourable region of the Ramachandran diagram is increased to about 90% in the refined structures from the 80 to 85% range in the previously reported structures. Our results not only provide significantly improved structures of the prion protein and hence would facilitate insights into its conversion in the spongiform encephalopathies, but also demonstrate the strong potential for using databases of known protein structures for structure determination and refinement.

关键词： Humans Proteins Databases Diseases Nuclear magnetic resonance Genetic mutations computational biology Brain Pathogens Amino acids

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Analysis of Protein Protein Dimeric Interfaces

Analysis of Protein Protein Dimeric Interfaces

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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Feihong Wu Fadi Towfic Drena Dobbs Vasant Honavar Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA

We analyzed the structural properties and the local surface environment of surface amino acid residues of proteins using a large, non-redundant dataset of 2383 protein chains in dimeric complexes from PDB. We compared the interface residues and non-interface residues based on six properties: side chain orientation, surface roughness, solid angle, ex value, hydrophobicity and interface cluster size. The results of our analysis show that interface residues have side chains pointing inward; interfaces are rougher, tend to be flat, moderately convex or concave and protrude more relative to non-interface surface residues. Interface residues tend to be surrounded by hydrophobic neighbors and tend to form clusters consisting of three or more interfaces residues. These findings are consistent with previous published studies using much smaller datasets, while allowing for more qualitative conclusions due to our larger dataset. Preliminary results suggest the possibility of using the six the properties to identify putative interface residues.

关键词： Proteins Rough surfaces Surface roughness bioinformatics Amino acids Solids Sequences Biomedical computing Computer interfaces Biomedical measurements

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Robocop: Multivariate state space model integrating epigenomic accessibility data to elucidate genome-wide chromatin occupancy 24th

Robocop: Multivariate state space model integrating epigenom...

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24th Annual Conference on Research in computational Molecular biology, RECOMB 2020

作者： Mitra, Sneha Zhong, Jianling MacAlpine, David M. Hartemink, Alexander J. Department of Computer Science Duke University DurhamNC27708 United States Program in Computational Biology and Bioinformatics Duke University DurhamNC27708 United States Department of Pharmacology and Cancer Biology Duke University Medical Center DurhamNC27710 United States Center for Genomic and Computational Biology Duke University DurhamNC27708 United States

ISBN: (纸本)9783030452568

Chromatin is the tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and level of occupancy of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. On the other hand, epigenomic accessibility data like ATAC-seq, DNase-seq, and MNase-seq provide insight into the chromatin landscape of all factors bound along the genome, but with minimal insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin information from epigenomic accessibility data with nucleotide sequence to compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors at once. RoboCOP can be applied to any epigenomic dataset that provides quantitative insight into chromatin accessibility in any organism, but here we apply it to MNase-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome. Using available protein-binding datasets from the literature, we show that our model more accurately predicts the binding of these factors genome-wide. © Springer Nature Switzerland AG 2020.

关键词： Hidden Markov models

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Super deduper, fast PCR duplicate detection in fastq files. 15

Super deduper, fast PCR duplicate detection in fastq files.

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6th ACM Conference on bioinformatics, computational biology, and Health Informatics, BCB 2015

作者： Petersen, Kristen R. Streett, David A. Gerritsen, Alida T. Hunter, Samuel S. Settles, Matthew L. Program in Bioinformatics and Computational Biology University of Idaho MoscowID83844-3051 United States Institute for Bioinformatics and Evolutionary Studies University of Idaho MoscowID83844-3051 United States Department of Biological Sciences University of Idaho MoscowID83844-3051 United States

ISBN: (纸本)9781450338530

Our goal was to explore the accuracy and utility of identifying and removing PCR duplicates from HTS data using Super Deduper. Super Deduper is a pre-alignment, sequence read based technique developed at the University of Idaho, which examines and uses only a small portion of each read's sequence in order to identify and remove PCR and/or optical duplicates. Through comparisons with well-known pre and post-alignment techniques, Super Deduper's parameters were optimized and its performance assessed. The results conclude that Super Deduper is a viable prealignment alternative to post-alignment techniques. Super Deduper is both independent of a reference genome and choice in alignment application, allowing for its use in a greater variety of HTS applications. Super Deduper is an open source application and can be found at https://***/dstreett/Super-Deduper. Copyright 2015 ACM.

关键词： Alignment

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ExpHTS: Analysis of high throughput sequence data in an experimental framework 15

ExpHTS: Analysis of high throughput sequence data in an expe...

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6th ACM Conference on bioinformatics, computational biology, and Health Informatics, BCB 2015

作者： Streett, David A. Petersen, Kristen R. Gerritsen, Alida T. Hunter, Samuel S. Settles, Matthew L. Program in Bioinformatics and Computational Biology University of Idaho MoscowID83844-3051 United States Institute for Bioinformatics and Evolutionary Studies University of Idaho MoscowID83844-3051 United States Department of Biological Sciences University of Idaho MoscowID83844-3051 United States

ISBN: (纸本)9781450338530

Analysis time and storage space are critical bottlenecks when analyzing multi-sample, comparative high throughput sequence experiments. The experimental High Throughput Sequencing (expHTS) pipeline mitigates these bottlenecks by streaming external application data, speeding analysis, and reducing storage space by eliminating intermediate, un-analyzed files. This creates faster run times, less storage space on the machine, and improves uniformity of sample analysis. Copyright 2015 ACM.

关键词： Pipelines

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Transcriptomic and Epigenomic Signatures of Liver Metabolism and Insulin Sensitivity in Aging Mice

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Mechanisms of ageing and development 2025年 225卷 112068页

作者： John T González Olivia H Scharfman Wanling Zhu Jessica Kasamoto Victoria Gould Rachel J Perry Albert T Higgins-Chen Department of Pathology Yale University School of Medicine New Haven CT USA. Department of Cellular & Molecular Physiology Yale School of Medicine New Haven CT USA Department of Endocrinology & Metabolism Yale School of Medicine New Haven CT USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT USA. Altos Labs Institute of Computation San Diego CA 92114 USA. Department of Endocrinology & Metabolism Yale School of Medicine New Haven CT USA. Electronic address: rachel.perry@yale.edu. Department of Pathology Yale University School of Medicine New Haven CT USA Program in Computational Biology and Bioinformatics Yale University New Haven CT USA Department of Psychiatry Yale School of Medicine New Haven CT USA. Electronic address: a.higginschen@yale.edu.

Age-related declines in insulin sensitivity and glucose metabolism contribute to metabolic disease. Despite the liver's central role in glucose homeostasis, a comprehensive phenotypic characterization and concurrent molecular analysis of insulin resistance and metabolic dysfunction in the aging liver is lacking. We characterized hepatic insulin resistance and mitochondrial metabolic defects through metabolic cage, hyperinsulinemic-euglycemic clamp, and tracer studies paired with transcriptomic and DNA methylation analyses in young and aged male mice. Aged mice exhibited benchmark measures of whole body and liver insulin resistance. Aged mice showed lower pyruvate dehydrogenase flux, decreased fatty acid oxidation and citrate synthase fluxes, and increased pyruvate carboxylase flux under insulin-stimulated conditions. Molecular analysis revealed age-related changes in metabolic genes Pck1, Socs3, Tbc1d4, and Enpp1. Unsupervised network analysis identified an intercorrelated phenotype module (ME-Glucose), RNA module, and DNA methylation module. The DNA methylation module was enriched for lipid metabolism pathways and TCF-1 binding, while the RNA module was enriched for MZF-1 binding and regulation by miR-155-5p. Protein-protein interaction network analysis revealed interactions between module genes and canonical metabolic pathways, highlighting genes including Ets1, Ppp1r3b, and Enpp3. This study reveals novel genes underlying age-related hepatic insulin resistance as potential targets for metabolic interventions to promote healthy aging.

关键词： DNA methylation Insulin resistance Metabolic flux analysis Mitochondrial dysfunction Tricarboxylic acid (TCA) cycle

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APPROXIMATE BAYESIAN INFERENCE OF DIRECTED ACYCLIC GRAPHS IN biology WITH FLEXIBLE PRIORS ON EDGE STATES

arXiv

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arXiv 2019年

作者： Martin, Evan A. Fu, Audrey Qiuyan The Bioinformatics and Computational Biology Program University of Idaho United States The Bioinformatics and Computational Biology Program Department of Mathematics and Statistical Science Institute for Modeling Collaboration and Innovation Institute for Interdisciplinary Data Sciences University of Idaho United States

Graphical models or networks describe the statistical dependence among multiple variables and are widely used in biology (e.g., gene regulatory networks). Under appropriate assumptions, directed edges may represent causal relationships. A key feature of a biological network is sparsity, defined by how likely an edge is present, of which we often have some knowledge. However, most existing Bayesian methods use priors for the entire graph, making it difficult to specify the level of sparsity. The few methods that use priors on edges estimate the two directions independently;the sum of the two probabilities can exceed 1. Here, we present baycn (BAYesian Causal Network), a novel approximate Bayesian method that represents a graph in terms of three states of edges: the two directions and edge absence, and specifies priors on these edge states. We design a pseudo Bayesian sampling algorithm for efficient inference. We apply baycn to two genomic problems: i) distinguishing direct and indirect target genes of genetic variants, using these variants as instrumental variables, and ii) inferring combinatorial binding of highly-correlated transcription factors in Drosophila. In both cases and in extensive simulations, our method demonstrates much improved accuracy over existing methods for the whole graph and for individual edges. Copyright © 2019, The Authors. All rights reserved.

关键词： Inference engines

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Cover Feature: Diversity Oriented Strategy (DOS) for the Efficient Synthesis of Benzofuro[2,3-b]pyridine Derivatives with Anticancer Activity (ChemMedChem 3/2025)

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ChemMedChem 2025年第3期20卷

作者： Reymark Ereje Jantana Yahuafai Theeranuch Jaroenchuensiri Patcharaporn Supakijjanusorn Sukanya Unson Borwornlak Toopradab Thanyada Rungrotmongkol Somsak Pianwanit Chanat Aonbangkhen Tanatorn Khotavivattana Center of Excellence in Natural Products Department of Chemistry Faculty of Science Chulalongkorn University Pathumwan Bangkok 10330 Thailand Department of Physical Sciences College of Science University of the Philippines Baguio Baguio City 2600 Philippines Clinical Research Section Division of Research and Academic Support National Cancer Institute Bangkok 10400 Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Pathumwan Bangkok 10330 Thailand Center of Excellence in Computational Chemistry Department of Chemistry Faculty of Science Chulalongkorn University Pathumwan Bangkok 10330 Thailand

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The anatomic determinants of conductive hearing loss secondary to tympanic membrane perforation

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Journal of Otology 2017年第3期12卷 125-131页

作者： David J.Carpenter Debara L.Tucci David M.Kaylie Dennis O.Frank-Ito Division of Head and Neck Surgery & Communication Sciences Department of Surgery Duke University Medical Center Durham NC USA Computational Biology & Bioinformatics PhD Program Duke University Durham NC USA Department of Mechanical Engineering and Materials Science Duke University Durham NC USA

Objectives: Recent studies have introduced middle ear volume(MEV) as a novel determinant of perforation-induced conductive hearing loss(CHL) in a mechanism driven by trans-tympanic membrane pressure differences. The primary aims of this preliminary report are to: 1) correlate CHL with perforation size; 2) describe the relationship between CHL and MEV; and 3) compare CHL across a range of cholesteatoma ***: A retrospective pilot study was performed in 31 subjects with audiometry indicative of conductive hearing loss, temporal bone CT scans,and no prior middle ear surgery. Perforation size and MEV were analyzed with respect to CHL in a cohort of 10 perforated ears with no cholesteatoma. CHLs were compared in 3 groups defined by extent of cholesteatoma ***: Ears with large and small perforations showed mean ABG values of 32.0 ± 15.7 dB and 16.0 ± 16.4 dB, respectively. A direct relationship was observed between MEV and CHL for ears with large perforations across all frequencies, whereas this relationship for small perforations was frequency-dependent. Finally, a statistically significant increase in CHL was found across ears with increasing cholesteatoma involvement at 1000 Hz(X^2(2) = 9.786, p = 0.008),2000 Hz(x^2(2) = 8.455, p = 0.015),and 4000 Hz(x^2(2)= 8.253, p = 0.016).Conclusions: These pilot data suggest that greater perforation-induced conductive hearing losses may be associated with larger perforation sizes and cholesteatoma. The correlation between MEV and CHL may require additional study.

关键词： Perforation-induced hearing loss Conductive hearing loss Middle ear volume Three-dimensional volume reconstruction

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Transcription Factor-Centric Approach to Identify Non-recurring Putative Regulatory Drivers in Cancer 26th

Transcription Factor-Centric Approach to Identify Non-recur...

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26th International Conference on Research in computational Molecular biology, RECOMB 2022

作者： Zhao, Jingkang Martin, Vincentius Gordân, Raluca Center for Genomic and Computational Biology Duke University DurhamNC27708 United States Program in Computational Biology and Bioinformatics Duke University DurhamNC27708 United States Department of Computer Science Duke University DurhamNC27708 United States Department of Biostatistics and Bioinformatics Duke University DurhamNC27708 United States Department of Molecular Genetics and Microbiology Duke University DurhamNC27708 United States

ISBN: (纸本)9783031047480

Recent efforts to sequence the genomes of thousands of matched normal-tumor samples have led to the identification of millions of somatic mutations, the majority of which are non-coding. Most of these mutations are believed to be passengers, but a small number of non-coding mutations could contribute to tumor initiation or progression, e.g. by leading to dysregulation of gene expression. Efforts to identify putative regulatory drivers rely primarily on information about the recurrence of mutations across tumor samples. However, in regulatory regions of the genome, individual mutations are rarely seen in more than one donor. Instead of using recurrence information, here we present a method to prioritize putative regulatory driver mutations based on the magnitude of their effects on transcription factor-DNA binding. For each gene, we integrate the effects of mutations across all its regulatory regions, and we ask whether these effects are larger than expected by chance, given the mutation spectra observed in regulatory DNA in the cohort of interest. We applied our approach to analyze mutations in a liver cancer data set with ample somatic mutation and gene expression data available. By combining the effects of mutations across all regulatory regions of each gene, we identified dozens of genes whose regulation in tumor cells is likely to be significantly perturbed by non-coding mutations. Overall, our results show that focusing on the functional effects of non-coding mutations, rather than their recurrence, has the potential to prioritize putative regulatory drivers and the genes they dysregulate in tumor cells. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Transcription factors

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