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B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

Genomics, Proteomics & bioinformatics 2012年第3期10卷 142-152页

作者： Fadi Towfic Shakti Gupta Vasant Honavar Shankar Subramaniam Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIA 50010USA Department of Bioengineering University of California at San DiegoLa JollaCA 92122USA

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Col- lectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG path- ways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches （e.g., gene coexpression network alignment algorithms） in elucidating biochemical pathways involved in complex signaling events in ceils.

关键词： Ligand recognition B-cells Gene coexpression network alignment

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Mapping Emergency Medicine Data to the Observational Medical Outcomes Partnership Common Data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency Data Registry

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JACEP Open 2025年第1期6卷 100016-100016页

作者： Cohen, Inessa Diao, Zihan Goyal, Pawan Gupta, Aarti Hawk, Kathryn Malcom, Bill Malicki, Caitlin Sharma, Dhruv Sweeney, Brian Weiner, Scott G. Venkatesh, Arjun Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Section for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States American College of Emergency Physicians Washington DC United States Department of Emergency Medicine Brigham and Women's Hospital Boston MA United States Center for Outcomes Research and Evaluation (CORE) Section of Cardiovascular Medicine Yale School of Medicine New Haven CT United States

Objectives: This study aims to conduct a gap analysis to determine the feasibility of mapping electronic health record data from the Clinical Emergency Data Registry (CEDR) to the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM). Methods: We employed a structured approach using a custom-built comparison matrix. This matrix facilitated the alignment of CEDR data fields with the corresponding elements in the OMOP-CDM schema. Each field was evaluated for compatibility, with categorization into 3 distinct types: direct matches, fields requiring transformation, and fields with no OMOP-CDM equivalent. The mapping process was informed by consultations with the Observational Health Data Sciences and Informatics community forums and was guided by existing documentation and best practices in data harmonization. We performed descriptive analyses, quantifying the extent of direct matches and identifying the specific transformations needed for each CEDR-CDM field to ensure compliance with the OMOP-CDM model. Results: Our analysis indicates a high degree of compatibility between CEDR and OMOP, with over 90% (244/269) of CEDR fields being successfully mapped. Specifically, 173 fields had direct matches, whereas 71 required transformations. Challenges identified include addressing fields unique to CEDR with no OMOP-CDM equivalent and managing the transformations required for proper alignment. Conclusion: The OMOP-CDM presents a promising framework for standardizing emergency medicine data, thereby enhancing future query automation, analytics, and cross-institutional collaboration. Despite the potential challenges in capturing unique CEDR fields and addressing necessary transformations, most emergency department data can be standardized within the OMOP-CDM, fostering broader insights and applications in research and public health. © 2024 The Author(s)

关键词： databases electronic health records emergency service informatics opioid/adverse effects quality of health care registries

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Phytohormone signaling pathway analysis method for comparing hormone responses in plant-pest interactions

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BMC Research Notes 2012年第1期5卷 1-7页

作者： Studham, Matthew E. MacIntosh, Gustavo C. Bioinformatics and Computational Biology Program Iowa State University Ames IA 50011 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50011 United States

Background: Phytohormones mediate plant defense responses to pests and pathogens. In particular, the hormones jasmonic acid, ethylene, salicylic acid, and abscisic acid have been shown to dictate and fine-tune defense responses, and identification of the phytohormone components of a particular defense response is commonly used to characterize it. Identification of phytohormone regulation is particularly important in transcriptome analyses. Currently there is no computational tool to determine the relative activity of these hormones that can be applied to transcriptome analyses in soybean. Findings: We developed a pathway analysis method that provides a broad measure of the activation or suppression of individual phytohormone pathways based on changes in transcript expression of pathway-related genes. The magnitude and significance of these changes are used to determine a pathway score for a phytohormone for a given comparison in a microarray experiment. Scores for individual hormones can then be compared to determine the dominant phytohormone in a given defense response. To validate this method, it was applied to publicly available data from previous microarray experiments that studied the response of soybean plants to Asian soybean rust and soybean cyst nematode. The results of the analyses for these experiments agreed with our current understanding of the role of phytohormones in these defense responses. Conclusions: This method is useful in providing a broad measure of the relative induction and suppression of soybean phytohormones during a defense response. This method could be used as part of microarray studies that include individual transcript analysis, gene set analysis, and other methods for a comprehensive defense response characterization. © 2012 Studham and MacIntosh;licensee BioMed Central Ltd.

关键词： Salicylic Acid Jasmonic Acid Soybean Cyst Nematode Soybean Aphid Salicylic Acid Pathway

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An analysis of conformational changes upon RNA-Protein binding 14

An analysis of conformational changes upon RNA-Protein bindi...

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5th ACM Conference on bioinformatics, computational biology, and Health Informatics, ACM BCB 2014

作者： Sankar, Kannan Jernigan, Robert L. Walia, Rasna R. Honavar, Vasant G. Mann, Carla M. Dobbs, Drena Bioinformatics and Computational Biology Program Dept. of Biochem. Biophysics and Molecular Biology Iowa State University United States Dept. of Biochem. L.H. Baker Center for Bioinformatics and Biological Statistics Iowa State University United States Bioinformatics and Computational Biology Program Dept. of Computer Science Iowa State University United States Bioinformatics and Genomics Program College of Information Sciences and Technology Pennsylvania State University United States Dept. of Genetics Development and Cell Biology L.H. Baker Center for Bioinformatics Iowa State University United States

ISBN: (纸本)9781450328944

RNA-binding proteins (RBPs) have myriad functions in transcription, translation, and post-transcriptional gene regulation, with central roles in normal development as well as in both genetic and infectious diseases. When a protein binds RNA, a conformational change often occurs. For RNA-protein complexes that have been characterized, conformational changes have been observed in the protein, the RNA, or both. These conformational changes have not been sufficiently characterized, however, in part due to the small number of structures of bound and unbound complexes of RNA-binding proteins available until recently. Here we systematically analyze a new dataset of 90 pairs of bound and unbound proteins to evaluate the conformational changes that occur upon RNA binding. Most of the conformational changes were observed in noninterfacial regions of the RNA-binding proteins. Detailed analyses of the modes of RNA binding and any associated conformational changes in proteins are critical for fully understanding the mechanisms of RNA-protein recognition, for developing better RNA-protein docking methods and methods for predicting interfacial residues, and for RNA-based drug design. Copyright © 2014 ACM.

关键词： RNA

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ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types

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Genome biology 2025年第1期26卷 1-30页

作者： Dincer, Tevfik Umut Ernst, Jason Bioinformatics Interdepartmental Program University of California Los Angeles Los Angeles 90095 CA United States Department of Biological Chemistry University of California Los Angeles Los Angeles 90095 CA United States Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at University of California Los Angeles Los Angeles 90095 CA United States Computer Science Department University of California Los Angeles Los Angeles 90095 CA United States Jonsson Comprehensive Cancer Center University of California Los Angeles Los Angeles 90095 CA United States Molecular Biology Institute University of California Los Angeles Los Angeles 90095 CA United States Department of Computational Medicine University of California Los Angeles Los Angeles 90095 CA United States

We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types. © The Author(s) 2025.

关键词： CRISPR screens Epigenome Gene regulation Genome annotation Hidden Markov model Machine learning Massively parallel reporter assays

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MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

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BMC Research Notes 2010年第1期3卷 1-9页

作者： Sucaet, Yves Wurtele, Eve Syrkin Department of Genetics Development and Cell Biology Iowa State University Ames IA 50011 United States Interdepartmental Program in Bioinformatics and Computational Biology Iowa State University Ames IA 50011 United States

Background. Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results. MetNetAPI is a versatile Application programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions. An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, *** and R programming environments and offers flexible query and bro

关键词： Application program Interface Molecular Entity Biological Database Command Line Interface Network Object

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Genetic correlates of autoreactivity and autoreactive potential in human Ig heavy chains

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Immunome Research 2009年第1期5卷 1-8页

作者： Volpe, Joseph M Kepler, Thomas B Center for Computational Immunology Duke University Durham NC United States Departments of Biostatistics and Bioinformatics and Immunology Duke University Medical Center Durham NC United States Computational Biology and Bioinformatics Graduate Program Institute for Genome Sciences and Policy Duke University Durham NC United States

Background. Immature bone marrow B cells are known to have longer CDR3 than mature peripheral B cells, and this genetic characteristic has been shown to correlate with autoreactivity in these early cells. B-cell Central tolerance eliminates these cells, but it is known that autoreactive B cells nevertheless appear commonly in healthy human blood. We examined over 7,300 Ig genes from Genbank, including those annotated by their discoverers as associated with autoreactivity, to determine the genetic correlates of autoreactivity in mature B cells. Results. We find differential biases in gene segment usage and higher mutation frequency in autoreactivity-associated Ig genes, but the CDR3 lengths do not differ between autoreactive and non-autoreactive Ig genes. The most striking genetic signature of autoreactivity is an increase in the proportion of N-nucleotides relative to germline-encoded nucleotides in CDR3 from autoreactive genes. Conclusion. We hypothesize that peripheral autoreactivity results primarily from somatic mutation, and that the genetic correlates of autoreactivity in mature B-cells are not the same as those for autoreactivity in immature B cells. What is seen in mature autoreactive B cells are the correlates of autoreactive potential, not of autoreactivity per se. The autoreactive potential is higher for V(D)J rearrangements encoded to a large extent by N-nucleotides rather than by the gene segments that, we posit, have been selected in germline evolution for their suppression of autoreactive potential.

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BPS2025 - Cross-scale conundrum: Slow masticatory myosin in jaw muscles that are both fast and strong

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Biophysical Journal 2025年第3期124卷 516a-516a页

作者： Varun V. Dhorajia Nicholas LaFave Brandon Reder Robert Brocklehurst Nicolai Konow Sam Walcott Jeffrey R. Moore Biomedical Engineering and Biotechnology Program University of Massachusetts Lowell Lowell MA USA Department of Biological Sciences University of Massachusetts Lowell Lowell MA USA Department of Mathematical Sciences Worcester Polytechnic Institute Worcester MA USA Department of Bioinformatics and Computational Biology Worcester Polytechnic Institute Worcester MA USA

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A Comparison of Lossless Compression Methods in Microscopy Data Storage Applications: Microscopy compression comparison 23

A Comparison of Lossless Compression Methods in Microscopy D...

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6th International Conference on Software Engineering and Information Management, ICSIM 2023

作者： Walker, Logan Alexander Li, Ye McGlothlin, Maggie Cai, Dawen University of Michigan Biophysics Program Department of Computational Medicine and Bioinformatics United States University of Michigan Cell and Developmental Biology United States University of Michigan Cell and Developmental Biology Biophysics Program Neuroscience United States

ISBN: (纸本)9781450398237

Modern high-throughput microscopy methods such as light-sheet imaging and electron microscopy can produce petabytes of data inside of a single experiment. Storage of these large images, however, is challenging because of the difficulty of moving, storing, and analyzing such vast amounts of data, which is often collected at very high data rates (>1GBps). In this report, we provide a comparison of the performance of several compression algorithms using a collection of published and unpublished datasets including confocal, fMOST, and pathology images. We also use simulated data to demonstrate the efficiency of each algorithm as image content or entropy increases. As a result of this work, we recommend the use of the BLOSC algorithm combined with ZSTD for various microscopy applications, as it produces the best compression ratio over a collection of conditions. © 2023 ACM.

关键词： Information management

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Predicting dynamic cellular protein-RNA interactions by deep learning using in vivo RNA structures

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细胞研究（英文版） 2021年第5期31卷 495-516页

作者： Lei Sun Kui Xu Wenze Huang Yucheng T.Yang Pan Li Lei Tang Tuanlin Xiong Qiangfeng Cliff Zhang MOE Key Laboratory of Bioinformatics Beijing Advanced Innovation Center for Structural Biology and Frontier Research Center for Biological StructureCenter for Synthetic and Systems BiologySchool of Life SciencesTsinghua UniversityBeijing 100084China Tsinghua-Peking Center for Life Sciences Beijing 100084China Program in Computational Biology and Bioinformatics Yale UniversityNew HavenCT 06520USA Department of Molecular Biophysics and Biochemistry Yale UniversityNew HavenCT 06520USA

Interactions with RNA-binding proteins (RBPs) are integral to RNA function and cellular regulation,and dynamically reflect specific cellular ***,presently available tools for predicting RBP-RNA interactions employ RNA sequence and/or predicted RNA structures,and therefore do not capture their condition-dependent ***,after profiling transcriptome-wide in vivo RNA secondary structures in seven cell types,we developed PrismNet,a deep learning tool that integrates experimental in vivo RNA structure data and RBP binding data for matched cells to accurately predict dynamic RBP binding in various cellular *** results for 168 RBPs support its utility for both understanding CUP-seq results and largely extending such interaction data to accurately analyze additional cell ***,PrismNet employs an 'attention' strategy to computationally identify exact RBP-binding nucleotides,and we discovered enrichment among dynamic RBP-binding sites for structure-changing variants(riboSNitches),which can link genetic diseases with dysregulated RBP *** rich profiling data and deep learning-based prediction tool provide access to a previously inaccessible layer of cell-type-specific RBP-RNA interactions,with clear utility for understanding and treating human diseases.

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