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International Conference on German Conference on Bioinformatics, GCB 2014

作者： Videm, Pavankumar Rose, Dominic Costa, Fabrizio Backofen, Rolf Bioinformatics Group Department of Computer Science Albert-Ludwigs-University Freiburg Georges-Köhler-Allee 106 FreiburgD-79110 Germany Munich Germany Albert-Ludwigs-University Freiburg FreiburgD-79104 Germany Albert-Ludwigs-University Freiburg Habsburgerstr. 49 FreiburgD-79104 Germany Centre for Non-Coding RNA in Technology and Health University of Copenhagen Gronnegardsvej 3 Frederiksberg CDK-1870 Denmark

ISBN: (纸本)9783885796299

Sequence and secondary structure analysis can be used to assign putative functions to non-coding rnas. However sequence information is changed by post-transcriptional modifications and secondary structure is only a proxy for the true 3D conformation of the rna polymer. In order to tackle these issues we can extract a different type of description using the pattern of processing that can be observed through the traces left in small rna-seq reads data. To obtain an efficient and scalable procedure, we propose to encode expression profiles in discrete structures, and process them using fast graph-kernel techniques. We present BlockClust for both clustering and classification of small non-coding rna transcripts with similar processing patterns. We show how the proposed approach is scalable, accurate and robust across different organisms, tissues and cell lines. BlockClust was successfully applied on a comprehensive set of eukaryotic data. It is the first tool for eukaryotic non-coding rna analysis available on the galaxy framework.

关键词： Cell culture

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Discovering and Evaluating Organizational Knowledge from Textual Data: Application to Crisis Management

SSRN

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SSRN 2023年

作者： Grissa, Dhouha Andonoff, Eric Hanachi, Chihab Center for non-coding RNA in Technology and Health Department of Veterinary and Animal Science University of Copenhagen Frederiksberg C1870 Denmark Université Toulouse - Capitole IRIT 2 rue du Doyen Gabriel Marty Toulouse31042 France

Crisis management effectiveness relies mainly on the quality of the distributed human organization deployed for saving lives, limiting damage and reducing risks. Organizations set up in this context are not always predefined and static;they could evolve and new forms could emerge since actors, such as volunteers or NGO, could join dynamically to collaborate. To improve crisis resolution effectiveness, it is first important to understand, analyze and evaluate such dynamic organizations in order to adjust crisis management plans and ease coordination among actors. Giving a textual experience feedback from past crisis, the objective of this paper is to discover the organizational structure deployed in the considered crisis and then evaluate it according to a set of criteria. For that purpose, we combine in a coherent framework text and association rule mining for pattern discovery and annotation, and multi-agent system models and techniques for formally building and evaluating organizational structures. We present the OSminer algorithm that discovers association rules based on relevant textual patterns and then builds an organizational structure including three main relations between actors: power, control and coordination. A real-life case study, a flood crisis hitting the south west of France, serves as a basis for testing/experimenting our solution. The organizational structure, discovered in this case study, has 24 actors. Its evaluation indicates its efficiency, but shows that it is neither robust nor flexible. Our findings highlight the potential of our approach to discover and evaluate organizational structures from a text recording interactions between stakeholders in a crisis context. © 2023, The Authors. All rights reserved.

关键词： Association rules

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TISSUES 2.0: an integrative web resource on mammalian tissue expression (vol 2018, 2018)

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DATABASE-THE JOUrnaL OF BIOLOGICAL DATABASES AND CURATION 2018年第2018期2018卷 1-N.PAG页

作者： Palasca, Oana Santos, Alberto Stolte, Christian Gorodkin, Jan Jensen, Lars Juhl Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkCenter for non-coding RNA in Technology and Health Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkDepartment of Veterinary and Animal Sciences Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark New York Genome Center New York NY USA Center for non-coding RNA in Technology and Health Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkDepartment of Veterinary and Animal Sciences Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Correspondence may also be addressed to Jan Gorodkin. Email: gorodkin@rth.dk Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkCenter for non-coding RNA in Technology and Health Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Corresponding author: Tel: +45 35325025 Email: lars.juhl.jensen@cpr.ku.dk

Physiological and molecular similarities between organisms make it possible to translate findings from simpler experimental systems—model organisms—into more complex ones, such as human. This translation facilitates the understanding of biological processes under normal or disease conditions. Researchers aiming to identify the similarities and differences between organisms at the molecular level need resources collecting multi-organism tissue expression data. We have developed a database of gene-tissue associations in human, mouse, rat and pig by integrating multiple sources of evidence: transcriptomics covering all four species and proteomics (human only), manually curated and mined from the scientific literature. Through a scoring scheme, these associations are made comparable across all sources of evidence and across organisms. Furthermore, the scoring produces a confidence score assigned to each of the associations. The TISSUES database (version 2.0) is publicly accessible through a user-friendly web interface and as part of the STRING app for Cytoscape. In addition, we analyzed the agreement between datasets, across and within organisms, and identified that the agreement is mainly affected by the quality of the datasets rather than by the technologies used or organisms *** URL: http://***/

关键词： DATABASES TRANSCRIPTOMES PROTEOMICS

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The DrugPattern tool for drug set enrichment analysis and its prediction for beneficial effects of oxLDL on type 2 diabetes

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Journal of Genetics and Genomics 2018年第7期45卷 389-397页

作者： Chuanbo Huang Weili Yang Junpei wang Yuan Zhou Bin Geng Georgios Kararigas Jichun Yang Qinghua Cui Department of Biomedical Informatics Department of Physiology and Pathophysiology MOE Key Lab of Cardiovascular Sciences School of Basic Medical Sciences Center for Non-Coding RNA Medicine Peking UniversityBeijing 100191China School of Mathematics Sciences Huaqiao University Quanzhou 362021 China Hypertension Center Fuwai Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeState Key Laboratory of Cardiovascular Disease National Center for Cardiovascular Diseases Beijing 100037 China Charit-Universitatsmedizin Berlin. Corporate Member of Freie Universitat Berlin Humboldt-Universitat zu Berlin Berlin Institute of Health Institute of Gender in Medicine and Center for Cardiovascular Research. DZHK (German Centre for Cardiovascular Research) 10115 Berlin Germany Center of Bioinformatics Key Laboratory for Neuro-lnformation of Ministry of Education School of Life Science and Technology University of Electronic Science and Technology of China Chengdu 610054 China

Enrichment analysis methods, e.g., gene set enrichment analysis, represent one class of important bio- informatical resources for mining patterns in biomedical datasets. However, tools for inferring patterns and rules of a list of drugs are limited. In this study, we developed a web-based tool, DrugPattern, for drug set enrichment analysis. We first collected and curated 7019 drug sets, including indications, adverse reactions, targets, pathways, etc. from public databases. For a list of interested drugs, DrugPat- tern then evaluates the significance of the enrichment of these drugs in each of the 7019 drug sets. To validate DrugPattern, we employed it for the prediction of the effects of oxidized low-density lipoprotein （oxLDL）, a factor expected to be deleterious. We predicted that oxLDL has beneficial effects on some diseases, most of which were supported by evidence in the literature. Because DrugPattern predicted the potential beneficial effects of oxLDL in type 2 diabetes （T2D）, animal experiments were then performed to further verify this prediction. As a result, the experimental evidences validated the DrugPattern prediction that oxLDL indeed has beneficial effects on T2D in the case of energy restriction. These data confirmed the prediction accuracy of our approach and revealed unexpected protective roles for oxLDL in various diseases. This study provides a tool to infer patterns and rules in biomedical datasets based on drug set enrichment analysis.

关键词： Enrichment analysis Drug Data mining oxLDL Type 2 diabetes

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OUGENE： a disease associated over-expressed and under-expressed gene database

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Science Bulletin 2016年第10期61卷 752-754页

作者： Xiaoyong Pan Hong-Bin Shen Section for Animal Genetics Bioinformatics and Breeding Center for Non-Coding RNA in Technology and Health University of Copenhagen 1870 Frederiksberg Denmark Department of Disease Systems Biology Novo NordiskFoundation Center for Protein Research University ofCopenhagen 1870 Frederiksberg Denmark Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

Gene over-expression or under-expression is closely associated with human diseases, which contributes to phenotypic variations and diversity. To our best knowledge, there is no single open specific resource available to provide the association information between gene over- or under-expression and various diseases. In this study, we presented a comprehensive disease-associated over- and under-expressed gene database （OUGene） based on our proposed text mining pipeline and several open curated databases. It contains total 41,269 unique associa- tions between 7,238 over- or under-expressed genes and 1,480 diseases, which are supported by 81,974 evidence sentences from 56,442 articles. The OUGene is compre- hensive and covers most important therapeutic areas. Meanwhile a new scoring system is designed to rank the associations based on benchmarking against hand-curated data. OUGene provides an easy-of-use web interface for researchers to analyze these data and visualize the associ- ated networks, which can give insights to the complex relationships between over- and under-expressed genes and diseases at a system level. It is available at ***. ***/bioinf/OUGene/.

关键词： Text mining Gene over- and under-expression Disease Database

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Ribosomal modification protein rimK-like family member A activates betaine-homocysteine S-methyltransferase 1 to ameliorate hepatic steatosis

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Signal Transduction and Targeted Therapy 2024年第9期9卷 4048-4065页

作者： Han Yan Wenjun Liu Rui Xiang Xin Li Song Hou Luzheng Xu Lin Wang Dong Zhao Xingkai Liu Guoqing Wang Yujing Chi Jichun Yang Department of Physiology and Pathophysiology School of Basic Medical SciencesState Key Laboratory of Vascular Homeostasis and RemodelingCenter for Non-coding RNA MedicinePeking University Health Science CenterBeijing 100191China Department of Endocrinology The Second Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhou 310058China Medical and Health Analysis Center Peking UniversityBeijing 100191China Department of Hepatobiliary Surgery Xi-Jing HospitalFourth Military Medical UniversityXi’an 710032China Department of Endocrinology Beijing Luhe HospitalCapital Medical UniversityBeijing 101100China Department of Hepatobiliary and Pancreatic Surgery General Surgery CentreFirst Hospital of Jilin UniversityChangchun 130061China Key Laboratory of Pathobiology Ministry of Education College of Basic Medical SciencesJilin UniversityChangchun 130012China Department of Central Laboratory and Institute of Clinical Molecular Biology Department of GastroenterologyPeking University People’s HospitalBeijing 100044China Department of Cardiology Peking University Third HospitalBeijing 100191China

nonalcoholic fatty liver disease(NAFLD)is a serious threat to public health,but its underlying mechanism remains poorly *** screening important genes using Gene Importance Calculator(GIC)we developed previously,ribosomal modification protein rimK-like family member A(RIMKLA)was predicted as one essential gene but its functions remained largely *** current study determined the roles of RIMKLA in regulating glucose and lipid *** expression was reduced in livers of human and mouse with *** RIMKLA overexpression ameliorated steatosis and hyperglycemia in obese ***-specific RIMKLA knockout aggravated high-fat diet(HFD)-induced dysregulated glucose/lipid metabolism in ***,RIMKLA is a new protein kinase that phosphorylates betaine-homocysteine S-methyltransferase 1(BHMT1)at threonine 45(Thr45)*** phosphorylation at Thr45 and activation,BHMT1 eliminated homocysteine(Hcy)to inhibit the activity of transcription factor activator protein 1(AP1)and its induction on fatty acid synthase(FASn)and cluster of differentiation 36(CD36)gene transcriptions,concurrently repressing lipid synthesis and uptake in ***45 to alanine(T45A)mutation inactivated BHMT1 to abolish RIMKLA’s repression on Hcy level,AP1 activity,FASn/CD36 expressions,and lipid ***1 overexpression rescued the dysregulated lipid metabolism in RIMKLA-deficient *** summary,RIMKLA is a novel protein kinase that phosphorylates BHMT1 at Thr45 to repress lipid synthesis and *** obese condition,inhibition of RIMKLA impairs BHMT1 activity to promote hepatic lipid deposition.

关键词： metabolism hepatic homocysteine

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Maximizing output and recognizing autocatalysis in chemical reaction networks is NP-complete

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Journal of Systems Chemistry 2012年第1期3卷 1-9页

作者： Andersen, Jakob L. Flamm, Christoph Merkle, Daniel Stadler, Peter F. Department for Mathematics and Computer Science University of Southern Denmark DK-5230 Odense M Campusvej 55 Denmark Institute for Theoretical Chemistry University of Vienna A-1090 Wien Währingerstraße 17 Austria Bioinformatics Group Department of Computer Science Interdisciplinary Center for Bioinformatics D-04107 Leipzig Härtelstraße 16-18 Germany Max Planck Institute for Mathematics in the Sciences D-04103 Leipzig Inselstraße 22 Germany Fraunhofer Institute for Cell Therapy and Immunology D-04103 Leipzig Perlickstraße 1 Germany Center for non-coding RNA in Technology and Health University of Copenhagen DK-1870 Frederiksberg C Grønnegårdsvej 3 Denmark Santa Fe Institute Santa Fe NM 87501 1399 Hyde Park Rd. United States

Background: A classical problem in metabolic design is to maximize the production of a desired compound in a given chemical reaction network by appropriately directing the mass flow through the network. Computationally, this problem is addressed as a linear optimization problem over the flux cone. The prior construction of the flux cone is computationally expensive and no polynomial-time algorithms are known. Results: Here we show that the output maximization problem in chemical reaction networks is NP-complete. This statement remains true even if all reactions are monomolecular or bi-molecular and if only a single molecular species is used as influx. As a corollary we show, furthermore, that the detection of autocatalytic species, i.e., types that can only be produced from the influx material when they are present in the initial reaction mixture, is an NPcomplete computational problem. Conclusions: Hardness results on combinatorial problems and optimization problems are important to guide the development of computational tools for the analysis of metabolic networks in particular and chemical reaction networks in general. Our results indicate that efficient heuristics and approximate algorithms need to be employed for the analysis of large chemical networks since even conceptually simple flow problems are provably intractable. © 2012 Andersen et al.;licensee Chemistry Central Ltd.

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An intermediate level of abstraction for computational systems chemistry

arXiv

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arXiv 2017年

作者： Andersen, Jakob L. Flamm, Christoph Merkle, Daniel Stadler, Peter F. Earth-Life Science Institute Tokyo Institute of Technology Tokyo152-8550 Japan Department of Mathematics and Computer Science University of Southern Denmark Denmark Research Network Chemistry Meets Microbiology University of Vienna WienA-1090 Austria Institute for Theoretical Chemistry University of Vienna Austria Department of Computer Science University of Leipzig Germany Max Planck Institute for Mathematics in the Sciences Leipzig Germany Fraunhofer Institute for Cell Therapy and Immunology Leipzig Germany Center for non-coding RNA in Technology Health University of Copenhagen Denmark Santa Fe Institute Santa Fe United States

Computational techniques are required for narrowing down the vast space of possibilities to plausible prebiotic scenarios, since precise information on the molecular composition, the dominant reaction chemistry, and the conditions for that era are scarce. The exploration of large chemical reaction networks is a central aspect in this endeavour. While quantum chemical methods can accurately predict the structures and reactivities of small molecules, they are not efficient enough to cope with large-scale reaction systems. The formalization of chemical reactions as graph grammars provides a generative system, well grounded in category theory, at the right level of abstraction for the analysis of large and complex reaction networks. An extension of the basic formalism into the realm of integer hyperflows allows for the identification of complex reaction patterns, such as auto-catalysis, in large reaction networks using optimization techniques. Copyright © 2017, The Authors. All rights reserved.

关键词： Formal languages

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Microrna or not microrna?

MicroRNA or not microRNA?

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Lecture Notes in Computer Science

作者： Langenberger, David Bartschat, Sebastian Hertel, Jana Hoffmann, Steve Tafer, Hakim Stadler, Peter F. Bioinformatics Group Department of Computer Science University of Leipzig D-04107 Leipzig United Kingdom Interdisciplinary Center for Bioinformatics University of Leipzig Härtelstraße 16-18 D-04107 Leipzig Germany LIFE - Leipzig Research Center for Civilization Diseases University of Leipzig Germany Max Planck Institute for Mathematics in the Sciences Inselstraße 22 D-04103 Leipzig Germany Fraunhofer Institut für Zelltherapie und Immunologie Perlickstraße 1 D-04103 Leipzig Germany Department of Theoretical Chemistry University of Vienna Währingerstraße 17 A-1090 Wien Austria Center for Non-coding RNA in Technology and Health University of Copenhagen Grønnegårdsvej 3 DK-1870 Frederiksberg C Denmark Santa Fe Institute 1399 Hyde Park Rd. Santa Fe NM 87501 United States

ISBN: (纸本)9783642228247

The avalanche of next generation sequencing data has led to a rapid increase of annotated micrornas in the last few years. Many of them are specific to individual species or rather narrow clades. A closer inspection of the current version of miRBase shows that dozens of entries conflict with other ncrnas, in particular snornas. With few exceptions, these cases show little similarities to canonical micrornas, however, and thus they should be considered as mis-annotations. © 2011 Springer-Verlag.

关键词： rna

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