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International Joint Conference on Neural Networks (IJCNN)

作者： Feihong Wu B. Olson D. Dobbs V. Honavar Bioinformatics and Computational Biology Graduate Program Center for Computational Intelligence Learning and Discovery Iowa State University Ames IA USA

The ability to identify protein binding sites and to detect specific amino acid residues that contribute to the specificity and affinity of protein interactions has important implications for problems ranging from rational drug design to analysis of metabolic and signal transduction networks. Support vector machines (SVM) and related kernel methods offer an attractive approach to predicting protein binding sites. An appropriate choice of the kernel function is critical to the performance of SVM. Kernel functions offer a way to incorporate domain-specific knowledge into the classifier. We compare the performance of three types of kernels functions: identity kernel, sequence-alignment kernel, and amino acid substitution matrix kernel in the case of SVM classifiers for predicting protein-protein, protein-DNA and protein-RNA binding sites. The results show that the identity kernel is quite effective in on all three tasks. The substitution kernel based on amino acid substitution matrices that take into account structural or evolutionary conservation or physicochemical properties of amino acids yields modest improvement.

关键词： Kernel Proteins Amino acids Support vector machines Support vector machine classification Matrices Drugs Signal design Signal analysis Signal processing

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Diversity and Evolution of RNA Recognition Motifs: A Case Study on the Utility of RdRp in the phylum Duplornaviricota

Diversity and Evolution of RNA Recognition Motifs: A Case St...

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2023 IEEE International Conference on bioinformatics and Biomedicine, BIBM 2023

作者： Je, Mikyung Cho, Myeongji Son, Hyeon S. Seoul National University Interdisciplinary Graduate Program in Bioinformatics College of Natural Science Seoul Korea Republic of Seoul National University Lab. of Computational Biology & Bioinformatics Graduate School of Public Health Seoul Korea Republic of Seoul National University Institute of Health and Environment Seoul Korea Republic of

ISBN: (纸本)9798350337488

Viruses possess specific conserved regions known as RNA recognition motifs, which are shared within taxonomic groups. Applying these to the Baltimore virus classification system, there are genes/proteins that serve as biomarkers for each of the seven groups. Mutations in conserved sequence regions can have a significant impact on the function of a virus, especially if these conserved regions are part of a major protein. In this study, we analyzed the RdRp gene, known to be a representative RRM of RNA viruses, from viruses of five families (Alternaviridae, Chrysoviridae, Totiviridae, Sedoreoviridae, and Spinareoviridae) within the phylum Duplornaviricota. Data were retrieved from the NCBI non-redundant (nr) database (https://***/protein) applying a cut-off of 300 amino acids in length. RdRp protein sequences were aligned using PROMALS3D, and PhyML (v3.0) was used for phylogenetic analysis. In the next step, we utilized the officially provided ICTV taxonomy and bioinformatics tools to assign the phylogenetic position of RdRp. Although this analysis focused solely on RdRp, it can be concluded that using this gene as a marker may be sufficient for taxonomic assignment. Subsequent analyses will target DNA viruses and RT viruses to perform a more comprehensive assessment. This extensive analysis aims to validate the usefulness of marker genes in the overall viral taxonomy. © 2023 IEEE.

关键词： classification marker gene RdRp RNA recognition motif taxonomy virus

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Designing metabolic engineering strategies with genome-scale metabolic flux modeling

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Advances in Genomics and Genetics 2015年 5卷 93页

作者： Yen, Jiun Y Tanniche, Imen Fisher, Amanda K Gillaspy, Glenda E Bevan, David R Senger, Ryan S Department of Biological Systems Engineering Virginia Tech Department of Biochemistry Virginia Tech Genomics Bioinformatics and Computational Biology Interdisciplinary Program Virginia Tech

New in silico tools that make use of genome-scale metabolic flux modeling are improving the design of metabolic engineering strategies. This review highlights the latest developments in this area, explains the interface between these in silico tools and the experimental implementation tools of metabolic engineers, and provides a way forward so that in silico predictions can better mimic reality and more experimental methods can be considered in simulation studies. The several methodologies for solving genome-scale models (eg, flux balance analysis [FBA], parsimonious FBA, flux variability analysis, and minimization of metabolic adjustment) all have unique advantages and applications. There are two basic approaches to designing metabolic engineering strategies in silico, and both have demonstrated success in the literature. The first involves: 1) making a genetic manipulation in a model; 2) testing for improved performance through simulation; and 3) iterating the process. The second approach has been used in more recently designed in silico tools and involves: 1) comparing metabolic flux profiles of a wild-type and ideally engineered state and 2) designing engineering strategies based on the differences in these flux profiles. Improvements in genome-scale modeling are anticipated in areas such as the inclusion of all relevant cellular machinery, the ability to understand and anticipate the results of combinatorial enrichment experiments, and constructing dynamic and flexible biomass equations that can respond to environmental and genetic manipulations.

关键词： genome-scale modeling flux balance analysis flux variability analysis minimization of metabolic adjustment metabolic bottleneck pathway optimization

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Vertex-Frequency Clustering

Vertex-Frequency Clustering

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IEEE Data Science Workshop (DSW)

作者： Daniel B. Burkhardt Jay S. Stanley III Guy Wolf Smita Krishnaswamy Department of Genetics Computational Biology and Bioinformatics Program Department of Mathematics and Statistics Université de Montréal

We propose a novel approach for clustering the vertices of a graph. The method, Vertex-Frequency Clustering (VFC), considers the local harmonic content of one or many graph signals, forming partitions based on spectral features in the input signal. The method can be related to spectral clustering, and the length scale over which frequencies are considered is tunable. This allows one to cluster data based on intrinsic graph geometry in the context of signal dynamics. VFC is useful for unravelling active regions in a signal, collecting sets of similar observations, or detecting anomalies. We demonstrate the utility of VFC in synthetic and biological data, and show how VFC can be used to identify observations with similar feature sets and signal profiles.

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Determine the Populations of Protein Conformation States Using Experimental Residual Dipolar Coupling Data

Determine the Populations of Protein Conformation States Usi...

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第十七届国际生物物理大会;第十二届中国生物物理大会

作者： Santhosh K.Vammi Department of Computer Sciece Program of Bioinformatics and Computational biologyIowa State UniversityAmesIowaUSA

Ensembles have been increasingly used to represent the heterogeneity of protein native states and there is a number of exciting recent work that determines such ensembles using experimental *** what extent these ensembles represent the native states is debatable since the ensemble,which may contain over a hundred conformations,may be underconstrained by the experimental *** this work,we introduce a new feature,the

关键词： structure ensemble conformation states populations ubiquitin dynamics

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Admixture mapping analysis in the context of GWAS with GAW18 data

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BMC proceedings 2014年第Suppl 1期8卷 S3页

作者： Mengjie Chen Can Yang Cong Li Lin Hou Xiaowei Chen Hongyu Zhao Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Biostatistics Yale School of Public Health Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA

Admixture mapping is a disease-mapping strategy to identify disease susceptibility variants in an admixed population that is a result of mating between 2 historically separated populations differing in allele frequencies and disease prevalence. With the increasing availability of high-density genotyping data generated in genome-wide association studies, it is of interest to investigate how to apply admixture mapping in the context of the genome-wide association studies and how to adjust for admixture in association tests. In this study, we first evaluated 3 different local ancestry inference methods, LAMP, LAMP-LD, and MULTIMIX. Then we applied admixture mapping analysis based on estimated local ancestry. Finally, we performed association tests with adjustment for local ancestry.

关键词： Reference Panel Admixture Mapping Local Ancestry Native American Ancestry Human Genome Diversity Project

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Disagreement in middle ear volume estimation between tympanometry and three-dimensional volume reconstruction in the context of tympanic membrane perforation

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Journal of Otology 2017年第2期12卷 74-79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 SurgeryDuke University Medical CenterDurhamNCUSA Computational Biology&Bioinformatics PhD Program Duke UniversityDurhamNCUSA Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNCUSA

Introduction: Middle ear volume(MEV) is a clinically relevant parameter across middle ear diseases. MEV values between these techniques have never before been tested for agreement in ears with perforated tympanic membranes(TMs).Methods: Middle ears were identified from 36 patients ranging 18-89 years of age with TM perforations who underwent tympanometry and temporal bone computed tomography(CT) between 2005 and 2015. MEVs calculated by both tympanometry and three-dimensional volume reconstruction(3DVR) were analyzed for agreement using Bland Altman plots. The differences between tympanometric and 3DVR MEV values for each given middle ear were characterized across MEV quartiles(1= smallest; 4= largest) and across increasing states of middle ear disease using Kruskale Wallis and Wilcoxon testing with Bonferroni ***: Bland Altman plots demonstrated significant disagreement between MEV measurement techniques. Differences between tympanometric(T) and 3DVR MEV values were significantly greater with increasing average(i.e.(Tt3DVR)/2)) MEV per linear regression(p < 0.0001). Significance was demonstrated between fourth and first average MEV quartiles(p= 0.0024), fourth and second quartiles(p= 0.0024), third and first quartiles(p= 0.0048), and third and second quartiles(p= 0.048). Absolute MEV difference was not significantly different across varying states of middle ear disease(p= 0.44).Conclusion: Statistically and clinically significant disagreement was demonstrated between tympanometric and 3DVR MEV values. Studies that vary in MEV estimation techniques may be expected to demonstrate significantly different results. These preliminary results suggest that clinicians should endeavor to seek further confirmation when interpreting high tympanometric MEV values.

关键词： Middle ear volume Tympanometry Three-dimensional volume reconstruction Tympanic membrane perforation

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Unveiling the multifaceted domain polymorphism of the Menshen antiphage system

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Nucleic acids research 2025年第9期53卷 gkaf357页

作者： Huan Li Yongjun Tan Dwaipayan Basu Kevin D Corbett Dapeng Zhang Department of Biology College of Arts and Sciences Saint Louis University Saint Louis MO 63103 United States. Department of Chemistry and Biochemistry University of California San Diego La Jolla CA 92093 United States. Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA 92093 United States. Department of Molecular Biology University of California San Diego La Jolla CA 92093 United States. Program of Bioinformatics and Computational Biology School of Science and Engineering Saint Louis University Saint Louis MO 63103 United States.

Recent advances have significantly enriched our understanding of complex bacteria-phage interactions. To date, over one hundred bacterial antiphage systems have been identified, yet the mechanisms of many, including the recently discovered Menshen system, remain elusive. We employed comparative genomics and protein bioinformatics for a systematic investigation of the Menshen system, focusing on its organization, structure, function, and evolution. By delineating six primary domain determinants and predicting their functions, we propose that the three components (NsnA-B-C) of Menshen likely act as sensor, transducer, and effector modules, respectively. Notably, we unveil remarkable polymorphism in domain composition within both NsnA and NsnC. NsnA proteins universally share ParB-DUF262 and DNA-binding ParBDB domains, and often include additional DNA-binding modules at their N-termini. NsnC effectors exhibit diverse inactive PIN (inPIN)-like domains for target recognition in their N-termini, and multiple nuclease domains for toxicity in their C-termini. We demonstrate that this multifaceted polymorphism results from the independent integration of various sensor domains into NsnA, alongside constant shuffling and diversification of the inPIN and effector domains in NsnC. These findings not only elucidate the functional diversity and inter-subunit interactions of the Menshen system, but also underscore its exceptional capacity for adaptability and versatility in the ongoing arms race between bacteria and phages.

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Geometry based data generation 32

Geometry based data generation

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32nd Conference on Neural Information Processing Systems, NeurIPS 2018

作者： Lindenbaum, Ofir Wolf, Guy Stanley, Jay S. Krishnaswamy, Smita Applied Mathematics Program Yale University New HavenCT06511 United States Computational Biology and Bioinformatics Program Yale University New HavenCT06510 United States Departments of Genetics and Computer Science Yale University New HavenCT06510 United States

We propose a new type of generative model for high-dimensional data that learns a manifold geometry of the data, rather than density, and can generate points evenly along this manifold. This is in contrast to existing generative models that represent data density, and are strongly affected by noise and other artifacts of data collection. We demonstrate how this approach corrects sampling biases and artifacts, thus improves several downstream data analysis tasks, such as clustering and classification. Finally, we demonstrate that this approach is especially useful in biology where, despite the advent of single-cell technologies, rare subpopulations and gene-interaction relationships are affected by biased sampling. We show that SUGAR can generate hypothetical populations, and it is able to reveal intrinsic patterns and mutual-information relationships between genes on a single-cell RNA sequencing dataset of hematopoiesis. © 2018 Curran Associates Inc..All rights reserved.

关键词： Genes

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Influence of conformational change of chain unit on the intrinsic negative thermal expansion of polymers

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Chinese Chemical Letters 2021年第4期32卷 1515-1518页

作者： Qiangsheng Sun Ke Jin Yuhui Huang Jia Guo Thanyada Rungrotmongkol Phornphimon Maitarad Changchun Wang State Key Laboratory of Molecular Engineering of Polymers and Department of Macromolecular Science Fudan UniversityShanghai 200433.China Biocatalyst and Environmental Biotechnology Research Unit Department of BiochemistryFaculty of Science and Program in Bioinformatics and Computational BiologyGraduate SchoolChulalongkom UniversityBangkok 10330Thailand Research Center of Nano Science and Technology Shanghai UniversityShanghai 200444China

Negative thermal expansion(NTE) behavior has roused wide interest for the control of thermomechanical properties of functional *** NTE behaviors have been found in kinds of compounds,it remains challenging for polymers to achieve intrinsic NTE *** this work,we systematically studied the conformational change of dibenzocyclooctadiene(DBCOD) derivatives between chair(C) and twist-boat(TB) forms based on density-functional theo ry(DFT) calculations,and found clear evidence of the relationship between the structure of DBCOD units and the thermal contraction behavior of the related *** order to obtain the polymer with NTE property,two conditions should be met for the thermal contracting DBCOD related units as follows:(i) the TB conformation can turn into C conformation as the temperature increases,and(ii) the volume of C conformation is smaller than that of TB *** rule should offer a guidance to exploration of the new intrinsic NTE polymers in the future.

关键词： Negative thermal expansion Conformational change Polyarylamides Density-functional theory Dibenzocyclooctadiene

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