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Meeting Report from the Second "Minimum Information for Biological and biomedical Investigations" (MIBBI) workshop

Standards in genomic sciences 2010年第3期3卷 259-66页

作者： Carsten Kettner Dawn Field Susanna-Assunta Sansone Chris Taylor Jan Aerts Nigel Binns Andrew Blake Cedrik M Britten Ario de Marco Jennifer Fostel Pascale Gaudet Alejandra González-Beltrán Nigel Hardy Jan Hellemans Henning Hermjakob Nick Juty Jim Leebens-Mack Eamonn Maguire Steffen Neumann Sandra Orchard Helen Parkinson William Piel Shoba Ranganathan Philippe Rocca-Serra Annapaola Santarsiero David Shotton Peter Sterk Andreas Untergasser Patricia L Whetzel Beilstein-Institut Frankfurt am Main Germany Centre for Ecology & Hydrology UK Oxford e-Research Centre University of Oxford UK The European Bioinformatics Institute (EBI) UK Faculty of Engineering - ESAT/SCD Leuven University Leuven-Heverlee Belgium Division of Pathway Medicine University of Edinburgh Medical School Edinburgh UK MRC Harwell UK Medical Department University Medical Center Johannes Gutenberg University-Mainz Mainz Germany Consortium for Genomic Technology Milano Italy University of Nova Gorica Nova Gorica Slovenia NIEHS NIH US National Toxicology Program USA Swiss Institute of Bioinformatics Geneva Switzerland Computational and Systems Medicine and Department of Computer Science University College London London UK Department of Computer Science Aberystwyth University Aberystwyth UK Center for Medical Genetics Ghent University Ghent Belgium Department of Plant Biology University of Georgia Athens USA Department of Stress- and Developmental Biology Institute for Plant Biochemistry Halle Germany Peabody Museum of Natural History Yale University New Haven USA Macquarie University Sydney Australia National University of Singapore Singapore Cancer Pharmacology The Mario Negri Institute for Pharmacological Research Milan Italy Image Bioinformatics Research Group Department of Zoology University of Oxford Oxford UK Wellcome Trust Sanger Institute UK Zentrum für Molekulare Biologie der Universität Heidelberg Heidelberg Germany The National Center for Biomedical Ontology / Stanford Center for Biomedical Informatics Research Stanford University Stanford USA

This report summarizes the proceedings of the second workshop of the 'Minimum Information for Biological and biomedical Investigations' (MIBBI) consortium held on Dec 1-2, 2010 in Rüdesheim, Germany through the sponsorship of the Beilstein-Institute. MIBBI is an umbrella organization uniting communities developing Minimum Information (MI) checklists to standardize the description of data sets, the workflows by which they were generated and the scientific context for the work. This workshop brought together representatives of more than twenty communities to present the status of their MI checklists and plans for future development. Shared challenges and solutions were identified and the role of MIBBI in MI checklist development was discussed. The meeting featured some thirty presentations, wide-ranging discussions and breakout groups. The top outcomes of the two-day workshop as defined by the participants were: 1) the chance to share best practices and to identify areas of synergy; 2) defining a series of tasks for updating the MIBBI Portal; 3) reemphasizing the need to maintain independent MI checklists for various communities while leveraging common terms and workflow elements contained in multiple checklists; and 4) revision of the concept of the MIBBI Foundry to focus on the creation of a core set of MIBBI modules intended for reuse by individual MI checklist projects while maintaining the integrity of each MI project. Further information about MIBBI and its range of activities can be found at http://***/.

关键词： Minimum Information European bioinformatics Institute biomedical Ontology Stable Link Breakout Group

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Perspective on recent developments and challenges in regulatory and systems genomics

arXiv

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arXiv 2024年

作者： Zeiltinger, Julia Roy, Sushmita Ay, Ferhat Mathelier, Anthony Medina-Rivera, Alejandra Mahony, Shaun Sinha, Saurabh Ernst, Jason Stowers Institute for Medical Research Kansas CityMO64112 United States Department of Pathology & Laboratory Medicine The University of Kansas Medical Center Kansas CityKS66160 United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison Madison53715 United States Wisconsin Institute for Discovery University of Wisconsin-Madison Madison53715 United States Centers for Autoimmunity Inflammation and Cancer Immunotherapy La Jolla Institute for Immunology La Jolla CA United States Bioinformatics and Systems Biology Program University of California La Jolla San DiegoCA United States Department of Pediatrics University of California La Jolla San DiegoCA United States Nordic EMBL Partnership University of Oslo Oslo0318 Norway Department of Medical Genetics Institute of Clinical Medicine University of Oslo Oslo University Hospital Oslo Norway Department of Pharmacy University of Oslo Oslo Norway Laboratorio Internacional de Investigación sobre el Genoma Humano Universidad Nacional Autónoma de México Campus Juriquilla Blvd. Juriquilla 3001 Santiago de Querétaro76230 Mexico Center for Eukaryotic Gene Regulation Department of Biochemistry and Molecular Biology The Pennsylvania State University University ParkPA16802 United States Walter H. Coulter Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA United States H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology AtlantaGA United States Department of Biological Chemistry University of California Los Angeles Los AngelesCA90095 United States Computer Science Department University of California Los Angeles Los AngelesCA90095 United States Department of Computational Medicine University of California Los Angeles Los AngelesCA90095 United States Eli and Edythe Broad Center of Regenerative Medicine Stem Cell Research University of California Los Angeles Los AngelesCA90095 United States

Predicting how genetic variation affects phenotypic outcomes at the organismal, cellular, and molecular levels requires deciphering the cis-regulatory code, the sequence rules by which non-coding regions regulate genes. In this perspective, we discuss recent computational progress and challenges towards solving this fundamental problem. We describe how cis-regulatory elements are mapped and how their sequence rules can be learned and interpreted with sequence-to-function neural networks, with the goal of identifying genetic variants in human disease. We also discuss how studies of the 3D chromatin organization could help identifying long-range regulatory effects and how current methods for mapping gene regulatory networks could better describe biological processes. We point out current gaps in knowledge along with technical limitations and benchmarking challenges of computational methods. Finally, we discuss newly emerging technologies, such as spatial transcriptomics, and outline strategies for creating a more general model of the cis-regulatory code that is more broadly applicable across cell types and individuals. © 2024, CC BY-NC-SA.

关键词： Molecular docking

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High-Resolution Imaging of Human Viruses in Liquid Droplets

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Advanced materials (Deerfield Beach, Fla.) 2021年第37期33卷 e2103221页

作者： G M Jonaid William J Dearnaley Michael A Casasanta Liam Kaylor Samantha Berry Madeline J Dukes Michael S Spilman Jennifer L Gray Deborah F Kelly Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Department of Biomedical Engineering Pennsylvania State University University Park PA 16802 USA. Materials Research Institute Pennsylvania State University University Park PA 16802 USA. Center for Structural Oncology Pennsylvania State University University Park PA 16802 USA. Molecular Cellular and Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Protochips Inc. Morrisville NC 27560 USA. Direct Electron LP. San Diego CA 92128 USA.

Liquid-phase electron microscopy (LP-EM) is an exciting new area in the materials imaging field, providing unprecedented views of molecular processes. Time-resolved insights from LP-EM studies are a strong complement to the remarkable results achievable with other high-resolution techniques. Here, the opportunities to expand LP-EM technology beyond 2D temporal assessments and into the 3D regime are described. The results show new structures and dynamic insights of human viruses contained in minute volumes of liquid while acquired in a rapid timeframe. To develop this strategy, adeno-associated virus (AAV) is used as a model system. AAV is a well-known gene therapy vehicle with current applications involving drug delivery and vaccine development for COVID-19. Improving the understanding of the physical properties of biological entities in a liquid state, as maintained in the human body, has broad societal implications for human health and disease.

关键词： COVID-19 SARS-CoV-2 adeno-associated virus direct electron detector liquid-phase electron microscopy silicon nitride

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Author Correction: Predicting the efficiency of prime editing guide RNAs in human cells

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Nature biotechnology 2024年第3期42卷 529页

作者： Hui Kwon Kim Goosang Yu Jinman Park Seonwoo Min Sungtae Lee Sungroh Yoon Hyongbum Henry Kim Department of Pharmacology Yonsei University College of Medicine Seoul Republic of Korea. Brain Korea 21 Plus Project for Medical Sciences Yonsei University College of Medicine Seoul Republic of Korea. Center for Nanomedicine Institute for Basic Science (IBS) Seoul Republic of Korea. Graduate Program of Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University Seoul Republic of Korea. Electrical and Computer Engineering Seoul National University Seoul Republic of Korea. Interdisciplinary Program in Bioinformatics Seoul National University Seoul Republic of Korea. Graduate School of Data Science Seoul National University Seoul Republic of Korea. Department of Pharmacology Yonsei University College of Medicine Seoul Republic of Korea. hkim1@yuhs.ac. Brain Korea 21 Plus Project for Medical Sciences Yonsei University College of Medicine Seoul Republic of Korea. hkim1@yuhs.ac. Center for Nanomedicine Institute for Basic Science (IBS) Seoul Republic of Korea. hkim1@yuhs.ac. Graduate Program of Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University Seoul Republic of Korea. hkim1@yuhs.ac. Severance Biomedical Science Institute Yonsei University College of Medicine Seoul Republic of Korea. hkim1@yuhs.ac. Graduate Program of NanoScience and Technology Yonsei University Seoul Republic of Korea. hkim1@yuhs.ac.

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Cancer Informatics: Profiling Age-Related Epigenetic Markers of Stomach Adenocarcinoma in Young and Old Subjects

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Cancer Informatics 2015年 14卷

作者： Byoung-Chul Kim Hyoung Oh Jeong Daeui Park Chul-Hong Kim Eun Kyeong Lee Dae Hyun Kim Eunok Im Nam Deuk Kim Sunghoon Lee Byung Pal Yu Jong Bhak Hae Young Chung Molecular Inflammation Research Center for Aging Intervention Pusan National University Busan Republic of Korea.Interdisciplinary Research Program of Bioinformatics and Longevity Science Pusan National University Busan Republic of Korea. Genomictree Inc. Yuseong-gu Daejeon Republic of Korea. Molecular Inflammation Research Center for Aging Intervention Pusan National University Busan Republic of Korea. Personal Genomics Institute Genome Research Foundation Suwon Republic of Korea.BioMedical Engineering UNIST Ulsan Republic of Korea. Department of Physiology University of Texas Health Science Center at San Antonio San Antonio TX USA.

The purpose of our study is to identify epigenetic markers that are differently expressed in the stomach adenocarcinoma (STAD) condition. Based on data from The Cancer Genome Atlas (TCGA), we were able to detect an age-related difference in methylation patterns and changes in gene and miRNA expression levels in young (n = 14) and old (n = 70) STAD subjects. Our analysis identified 323 upregulated and 653 downregulated genes in old STAD subjects. We also found 76 miRNAs with age-related expression patterns and 113 differentially methylated genes (DMGs), respectively. Our further analysis revealed that significant upregulated genes (n = 35) were assigned to the cell cycle, while the muscle system process (n = 27) and cell adhesion-related genes (n = 57) were downregulated. In addition, by comparing gene and miRNA expression with methylation change, we identified that three upregulated genes (ELF3, IL1β, and MMP13) known to be involved in inflammatory responses and cell growth were significantly hypomethylated in the promoter region. We further detected target candidates for age-related, downregulated miRNAs (hsa-mir-124-3, hsa-mir-204, and hsa-mir-125b-2) in old STAD subjects. This is the first report of the results from a study exploring age-related epigenetic biomarkers of STAD using high-throughput data and provides evidence for a complex clinicopathological condition expressed by the age-related STAD progression.

关键词： stomach adenocarcinoma age TCGA RNAseq miRNA DNA methylation

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Author Correction: Division of labour between Myc and G1 cyclins in cell cycle commitment and pace control

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Nature communications 2018年第1期9卷 4766页

作者： Peng Dong Manoj V Maddali Jaydeep K Srimani François Thélot Joseph R Nevins Bernard Mathey-Prevot Lingchong You Computational Biology and Bioinformatics Program Duke University Durham North Carolina 27708 USA. Department of Biomedical Engineering Duke University Durham North Carolina 27708 USA. School of Medicine Johns Hopkins University Baltimore Maryland 21205 USA. Department of Pharmacology and Cancer Biology Duke University Durham North Carolina 27708 USA. Department of Molecular Genetics and Microbiology Duke University Durham North Carolina 27708 USA. Department of Pharmacology and Cancer Biology Duke University Durham North Carolina 27708 USA. bernard.mathey-prevot@duke.edu. Department of Pediatrics Duke University Durham North Carolina 27708 USA. bernard.mathey-prevot@duke.edu. Department of Biomedical Engineering Duke University Durham North Carolina 27708 USA. you@duke.edu. Center for Genomic and Computational Biology Duke University Durham North Carolina 27708 USA. you@duke.edu. Duke Center for Systems Biology Duke University Durham North Carolina 27708 USA. you@duke.edu.

This Article contains errors in Supplementary Table 3, which are described in the Author Correction associated with this Article. The simulation results in the Article were based on the correct formula and thus the results are not affected by this correction. The errors have not been fixed in the original Article.

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scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs

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Cell systems 2023年第4期14卷 302-311.e4页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Yu-Te Lin Cristhian Roman-Vicharra Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Department of Nutrition and the Program in Integrative Nutrition & Complex Diseases Texas A&M University College Station TX 77843 USA. Electronic address: r-chapkin@tamu.edu. Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA. Electronic address: jcai@tamu.edu.

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

关键词： cell-cell interaction cellular communication gene regression network machine learning manifold alignment neural networks scRNA-seq single-cell RNA sequencing

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Author Correction: Lipid exposure activates gene expression changes associated with estrogen receptor negative breast cancer

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NPJ breast cancer 2023年第1期9卷 11页

作者： Shivangi Yadav Ranya Virk Carolina H Chung Mariana Bustamante Eduardo David VanDerway Duojiao Chen Kirsten Burdett Hongyu Gao Zexian Zeng Manish Ranjan Gannon Cottone Xiaoling Xuei Sriram Chandrasekaran Vadim Backman Robert Chatterton Seema Ahsan Khan Susan E Clare Department of Surgery Feinberg School of Medicine Northwestern University Chicago IL 60611 USA. Department of Biomedical Engineering Northwestern University Evanston IL 60208-2850 USA. Department of Biomedical Engineering University of Michigan Ann Arbor MI 48109 USA. Center of for Medical Genomics Indiana University School of Medicine Indianapolis IN 46202 USA. Department of Preventive Medicine Northwestern University Chicago IL 60611 USA. Department of Data Sciences Dana Farber Cancer Institute Harvard T.H. Chan School of Public Health Boston MA 02215 USA. Program in Chemical Biology University of Michigan Ann Arbor MI 48109 USA. Rogel Cancer Center University of Michigan Medical School Ann Arbor MI 48109 USA. Center for Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI 48109 USA. Department of Obstetrics and Gynecology Northwestern University Feinberg School of Medicine Chicago IL 60611 USA. Department of Surgery Feinberg School of Medicine Northwestern University Chicago IL 60611 USA. s-khan2@northwestern.edu. Department of Surgery Feinberg School of Medicine Northwestern University Chicago IL 60611 USA. susan.clare@northwestern.edu.

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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Hypoxia-responsive circular RNA circAAGAB reduces breast cancer malignancy by activating p38 MAPK and sponging miR-378 h

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Cancer cell international 2023年第1期23卷 45页

作者： Kuan-Yi Lee Chia-Ming Liu Li-Han Chen Chien-Yueh Lee Tzu-Pin Lu Li-Ling Chuang Liang-Chuan Lai Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan. Institute of Fisheries Science College of Life Science National Taiwan University Taipei Taiwan. Department of Life Science College of Life Science National Taiwan University Taipei Taiwan. Master Program for Biomedical Engineering College of Biomedical Engineering China Medical University Taichung Taiwan. Institute of Epidemiology and Preventive Medicine Department of Public Health National Taiwan University Taipei Taiwan. School of Physical Therapy and Graduate Institute of Rehabilitation Science College of Medicine Chang Gung University Taoyuan Taiwan. lchuang@gap.cgu.edu.tw. Department of Physical Medicine and Rehabilitation Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. lchuang@gap.cgu.edu.tw. Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan. llai@ntu.edu.tw. Bioinformatics and Biostatistics Core Center of Genomic and Precision Medicine National Taiwan University Taipei Taiwan. llai@ntu.edu.tw.

BACKGROUND:Breast cancer is a prevalent disease in women, with high prevalence worldwide. The hypoxic microenvironment of solid tumors develops during the progress of carcinogenesis and leads to greater malignancy and treatment resistance. Recently, accumulating evidence indicates that non-coding RNAs, such as circular RNAs (circRNAs), play a pivotal role in altering cellular functions. However, the underlying mechanisms of circRNAs in breast cancer are still unclear. Therefore, the purpose of this study was to investigate the role of a tumor-suppressive circRNA, circAAGAB, in breast cancer by assuming down-regulation of circAAGAB under hypoxia and the properties of a tumor suppressor. METHODS:Firstly, circAAGAB was identified from expression profiling by next generation sequencing. Next, the stability of circAAGAB increased by interacting with the RNA binding protein FUS. Moreover, cellular and nuclear fractionation showed that most circAAGAB resided in the cytoplasm and that it up-regulated KIAA1522, NKX3-1, and JADE3 by sponging miR-378 h. Lastly, the functions of circAAGAB were explored by identifying its down-stream genes using Affymetrix microarrays and validated by in vitro assays. RESULTS:The results showed that circAAGAB reduced cell colony formation, cell migration, and signaling through p38 MAPK pathway, as well as increased radiosensitivity. CONCLUSION:These findings suggest that the oxygen-responsive circAAGAB acts as a tumor suppressor in breast cancer, and may contribute to the development of a more specific therapeutic regimen for breast cancer.

关键词： Breast cancer Hypoxia Radiosensitivity Tumor suppressor circAAGAB miRNA sponge p38 MAPK

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