检索结果-内蒙古大学图书馆

Large-scale study of long non-coding rna functions based on structure and expression features

Science China(Life Sciences) 2013年第10期56卷 953-959页

作者： ZHAO Yi WANG Jian CHEN XiaoWei LUO HaiTao ZHAO YunJie XIAO Yi CHEN RenSheng Bioinformatics Research Group Advanced Computing Research LaboratoryInstitute of Computing TechnologyChinese Academy ofSciences Department of Physics Huazhong University of Science and Technology Laboratory of Bioinformatics and Non-coding RNA Institute of BiophysicsChinese Academy of Sciences

Mammals and other complex organisms can transcribe an abundance of long non-coding rnas(lncrnas)that fulfill a wide variety of regulatory roles in many biological *** roles,including as scaffolds and as guides for protein-coding genes,mainly depend on the structure and expression level of *** this review,we focus on the current methods for analyzing lncrna structure and expression,which is basic but necessary information for in-depth,large-scale analysis of lncrna functions.

关键词： non-coding rna structure expression function

来源：评论

学校读者我要写书评

暂无评论

PTMD: A Database of Human Disease-associated Post-translational Modifications

引用

Genomics, Proteomics & bioinformatics 2018年第4期16卷 244-251页

作者： Haodong Xu Yongbo Wang Shaofeng Lin Wankun Deng Di Peng Qinghua Cui Yu Xue Department of Bioinformatics & Systems Biology MOE Key Laboratory of Molecular Biophysics College of Life Science and Technology and the Collaborative Innovation Center for Biomedical Engineering Huazhong University of Science and Technology Department of Biomedical Informatics School of Basic Medical Sciences MOE Key Laboratory of Molecular Cardiovascular Sciences Center for Non-coding RNA Medicine Peking University

Various posttranslational modifications （PTMs） participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently implicated in human diseases. Therefore, an integral resource of PTM–disease associations （PDAs）would be a great help for both academic research and clinical use. In this work, we reported PTMD,a well-curated database containing PTMs that are associated with human diseases. We manually collected 1950 known PDAs in 749 proteins for 23 types of PTMs and 275 types of diseases from the literature. Database analyses show that phosphorylation has the largest number of disease associations, whereas neurologic diseases have the largest number of PTM associations. We classified all known PDAs into six classes according to the PTM status in diseases and demonstrated that the upregulation and presence of PTM events account for a predominant proportion of diseaseassociated PTM events. By reconstructing a disease–gene network, we observed that breast cancers have the largest number of associated PTMs and AKT1 has the largest number of PTMs connected to diseases. Finally, the PTMD database was developed with detailed annotations and can be a useful resource for further analyzing the relations between PTMs and human diseases. PTMD is freely accessible at http：//***.

关键词： Posttranslational modification Phosphorylation PTM-disease association Disease-gene network AKT1

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Proceedings of the EuBIC-MS 2020 Developers’ Meeting

引用

EuPA Open Proteomics 2020年 24卷 1-6页

作者： Christopher Ashwood Wout Bittremieux Eric W. Deutsch Nadezhda T. Doncheva Viktoria Dorfer Ralf Gabriels Vladimir Gorshkov Surya Gupta Andrew R. Jones Lukas Käll Dominik Kopczynski Lydie Lane Ludwig Lautenbacher Marc Legeay Marie Locard-Paulet Bart Mesuere Yasset Perez-Riverol Eugen Netz Sander Willems European Bioinformatics Community for Mass Spectrometry (info@***) Denmark Department of Cellular and Integrative Physiology University of Nebraska Medical Center Omaha USA Department of Computer Science University of Antwerp Antwerp Belgium Institute for Systems Biology Seattle WA 98109 USA Novo Nordisk Foundation Center for Protein Research University of Copenhagen Denmark Bioinformatics Research Group University of Applied Sciences Upper Austria Hagenberg Austria VIB-UGent Center for Medical Biotechnology VIB Ghent Belgium Department of Biochemistry and Molecular Biology University of Southern Denmark Denmark Institute of Systems Molecular and Integrative Biology University of Liverpool UK Science for Life Laboratory KTH - Royal Institute of Technology Solna Stockholm Sweden Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V. Dortmund Germany SIB-Swiss Institute of Bioinformatics and Department of Microbiology and Molecular Medicine Faculty of Medicine Geneva University Geneva Switzerland Technical University of Munich Chair for Proteomics and Bioanalytics Freising Germany European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Wellcome Trust Genome Campus Hinxton Cambridge CB10 1SD UK Applied Bioinformatics Dept. of Computer Science University of Tübingen Tübingen Germany Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA 92093 USA Center for non-coding RNA in Technology and Health Department of Veterinary and Animal Sciences University of Copenhagen Denmark Department of Biomolecular Medicine Ghent University Ghent Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium Biomolecular Interactions Max Planck Institute for Developmental Biology Tübingen Germany

The 2020 European bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers’ meeting was held from January 13 th to January 17 th 2020 in Nyborg, Denmark. Among the participants were scientists as well as developers working in the field of computational mass spectrometry (MS) and proteomics. The 4-day program was split between introductory keynote lectures and parallel hackathon sessions. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts, and to actively contribute to highly relevant research projects. We successfully produced several new tools that will be useful to the proteomics community by improving data analysis as well as facilitating future research. All keynote recordings are available on https://***/10.5281/zenodo.3890181 .

关键词： Computational mass spectrometry Mass spectrometry Proteomics bioinformatics Spectrum clustering Phosphoproteomics XIC extraction Proteomics graph networks Predicted spectra Metaproteomics Functional annotations Benchmark development

来源：评论

学校读者我要写书评

暂无评论

Regulation of cellular sterol homeostasis by the oxygen responsive noncoding rna lincNORS (vol 1, 4755, 2020)

引用

NATURE COMMUNICATIONS 2020年第1期11卷 4755-4755页

作者： Wu, Xue Niculite, Cristina M. Preda, Mihai Bogdan Rossi, Annalisa Tebaldi, Toma Butoi, Elena White, Mattie K. Tudoran, Oana M. Petrusca, Daniela N. Jannasch, Amber S. Bone, William P. Zong, Xingyue Fang, Fang Burlacu, Alexandrina Paulsen, Michelle T. Hancock, Brad A. Sandusky, George E. Mitra, Sumegha Fishel, Melissa L. Buechlein, Aaron Ivan, Cristina Oikonomopoulos, Spyros Gorospe, Myriam Mosley, Amber Radovich, Milan Dave, Utpal P. Ragoussis, Jiannis Nephew, Kenneth P. Mari, Bernard McIntyre, Alan Konig, Heiko Ljungman, Mats Cousminer, Diana L. Macchi, Paolo Ivan, Mircea Department of Microbiology and Immunology Indiana University School of Medicine Indianapolis IN 46202 USA Department of Medicine Indiana University School of Medicine Indianapolis IN 46202 USA “Victor Babes” National Institute of Pathology Bucharest Romania Institute of Cellular Biology and Pathology “Nicolae Simionescu” Bucharest Romania Laboratory of Molecular and Cellular Neurobiology Department of Cellular Computational and Integrative Biology - CIBIO University of Trento Trento Italy Laboratory of Translational Genomics Department of Cellular Computational and Integrative Biology - CIBIO University of Trento Trento Italy Yale Cancer Center Yale University School of Medicine New Haven CT 06520 USA The Oncology Institute “Prof Dr. Ion Chiricuta” Cluj-Napoca Romania Metabolite Profiling Facility Bindley Bioscience Center Purdue University West Lafayette IN 47907 USA Department of Genetics Department of Systems Pharmacology and Translational Therapeutics Institute of Translational Medicine and Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA 19104 USA Department of Cellular and Integrative Physiology Indiana University School of Medicine Indianapolis IN USA Departments of Radiation Oncology and Environmental Health Sciences Center for RNA Biomedicine University of Michigan Ann Arbor MI 48109 USA Department of Surgery Indiana University School of Medicine Indianapolis IN 46202 USA Department of Pathology and Laboratory Medicine Indiana University School of Medicine Indianapolis IN 46202 USA Melvin and Bren Simon Cancer Center Indiana University Indianapolis IN USA Department of Obstetrics and Gynecology Indiana University School of Medicine Indianapolis IN 46202 USA Department of Pharmacology and Toxicology Department of Pediatrics Wells Center for Pediatric Research Indiana University School of Medicine Indianapolis IN 46202 USA Indiana University Center for Genomics and Bioinformatics Bloomington IN 47405 USA Center

We hereby provide the initial portrait of lincNORS, a spliced lincrna generated by the MIR193BHG locus, entirely distinct from the previously described miR-193b-365a tandem. While inducible by low O2 in a variety of cells and associated with hypoxia in vivo, our studies show that lincNORS is subject to multiple regulatory inputs, including estrogen signals. Biochemically, this lincrna fine-tunes cellular sterol/steroid biosynthesis by repressing the expression of multiple pathway components. Mechanistically, the function of lincNORS requires the presence of RALY, an rna-binding protein recently found to be implicated in cholesterol homeostasis. We also noticed the proximity between this locus and naturally occurring genetic variations highly significant for sterol/steroid-related phenotypes, in particular the age of sexual maturation. An integrative analysis of these variants provided a more formal link between these phenotypes and lincNORS, further strengthening the case for its biological relevance. noncoding transcripts contribute to the adaptation of cellular processes to oxygen levels. Here the authors characterize a hypoxia responsive lncrna lincNORS and show that it has a role in cellular sterol homeostasis.

关键词： Long non-coding rnas Long non-coding rnas Homeostasis Homeostasis

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: Regulation of cellular sterol homeostasis by the oxygen responsive noncoding rna lincNORS

引用

Nature communications 2020年第1期11卷 5737页

作者： Xue Wu Cristina M Niculite Mihai Bogdan Preda Annalisa Rossi Toma Tebaldi Elena Butoi Mattie K White Oana M Tudoran Daniela N Petrusca Amber S Jannasch William P Bone Xingyue Zong Fang Fang Alexandrina Burlacu Michelle T Paulsen Brad A Hancock George E Sandusky Sumegha Mitra Melissa L Fishel Aaron Buechlein Cristina Ivan Spyros Oikonomopoulos Myriam Gorospe Amber Mosley Milan Radovich Utpal P Davé Jiannis Ragoussis Kenneth P Nephew Bernard Mari Alan McIntyre Heiko Konig Mats Ljungman Diana L Cousminer Paolo Macchi Mircea Ivan Department of Microbiology and Immunology Indiana University School of Medicine Indianapolis IN 46202 USA. Department of Medicine Indiana University School of Medicine Indianapolis IN 46202 USA. "Victor Babes" National Institute of Pathology Bucharest Romania. Institute of Cellular Biology and Pathology "Nicolae Simionescu" Bucharest Romania. Laboratory of Molecular and Cellular Neurobiology Department of Cellular Computational and Integrative Biology-CIBIO University of Trento Trento Italy. Laboratory of Translational Genomics Department of Cellular Computational and Integrative Biology-CIBIO University of Trento Trento Italy. Yale Cancer Center Yale University School of Medicine New Haven CT 06520 USA. The Oncology Institute "Prof Dr. Ion Chiricuta" Cluj-Napoca Romania. Metabolite Profiling Facility Bindley Bioscience Center Purdue University West Lafayette IN 47907 USA. Department of Genetics Department of Systems Pharmacology and Translational Therapeutics Institute of Translational Medicine and Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA 19104 USA. Department of Cellular and Integrative Physiology Indiana University School of Medicine Indianapolis IN USA. Departments of Radiation Oncology and Environmental Health Sciences Center for RNA Biomedicine University of Michigan Ann Arbor MI 48109 USA. Department of Surgery Indiana University School of Medicine Indianapolis IN 46202 USA. Department of Pathology and Laboratory Medicine Indiana University School of Medicine Indianapolis IN 46202 USA. Melvin and Bren Simon Cancer Center Indiana University Indianapolis IN USA. Department of Obstetrics and Gynecology Indiana University School of Medicine Indianapolis IN 46202 USA. Department of Pharmacology and Toxicology Department of Pediatrics Wells Center for Pediatric Research Indiana University School of Medicine Indianapolis IN 46202 USA. Indiana University Center for Genomics and Bioinformatics

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

关键词： Long non-coding rnas Homeostasis

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: Transcribed ultraconserved region 339 promotes carcinogenesis by modulating tumor suppressor micrornas

引用

Nature communications 2018年第1期9卷 160页

作者： Ivan Vannini Petra M Wise Kishore B Challagundla Meropi Plousiou Mirco Raffini Erika Bandini Francesca Fanini Giorgia Paliaga Melissa Crawford Manuela Ferracin Cristina Ivan Linda Fabris Ramana V Davuluri Zhiyi Guo Maria Angelica Cortez Xinna Zhang Lu Chen Shuxing Zhang Cecilia Fernandez-Cymering Leng Han Silvia Carloni Samanta Salvi Hui Ling Mariam Murtadha Paolo Neviani Barbara J Gitlitz Ite A Laird-Offringa Patrick Nana-Sinkam Massimo Negrini Han Liang Dino Amadori Amelia Cimmino George A Calin Muller Fabbri Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) S.r.l. IRCCS Gene Therapy Unit Meldola FC 47014 Italy. Departments of Pediatrics and Molecular Microbiology & Immunology Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Children's Center for Cancer and Blood Diseases and The Saban Research Institute Children's Hospital Los Angeles Los Angeles CA 90027 USA. Department of Biochemistry & Molecular Biology University of Nebraska Medical Center 985870 Nebraska Medical Center Omaha NE 68198 USA. Department of Internal Medicine Division of Pulmonary Allergy Critical Care and Sleep Medicine The Ohio State University Columbus OH 43210 USA. Department of Experimental Diagnostic and Specialty Medicine- DIMES University of Bologna Bologna 40126 Italy. Department of Experimental Therapeutics The University of Texas MD Anderson Cancer Center Houston TX 77030 USA. The Center for RNA Interference and Non-coding RNAs The University of Texas MD Anderson Cancer Center Houston TX USA. Departments of Preventive Medicine and Neurological Surgery Northwestern University-Feinberg School of Medicine Chicago IL 60611 USA. Department of Experimental Radiation Oncology The University of Texas MD Anderson Cancer Center Houston TX 77030 USA. Department of Gynecologic Oncology and Reproductive Medicine The University of Texas MD Anderson Cancer Center Houston TX 77030 USA. Integrated Molecular Discovery Laboratory Department of Experimental Therapeutics The University of Texas MD Anderson Cancer Center Houston TX 77030 USA. Division of Pre-Clinical Innovation National Center for Advancing Translational Sciences (NCATS) Rockville MD 20850 USA. Department of Molecular Virology Immunology and Medical Genetics Comprehensive Cancer Center Ohio State University Columbus OH 43210 USA. Department of Biochemistry and Molecular Biology McGovern Medical School The University of Texas Health Science Center at Hou

In the originally published version of this Article, the positions of the final two authors in the author list were inadvertently inverted during the production process. This error has now been corrected in both the P...

关键词：

来源：评论

学校读者我要写书评

暂无评论

Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

引用

BMC bioinformatics 2016年第Sup3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Bart Cuypers Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca NY USA Graduate Field of Computational Biology Cornell University Ithaca NY USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Nationalestraat 155 2000 Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Middelheimlaan 1 2020 Antwerpen Belgium Department of Computer Science University of Arizona Tucson AZ 84721 USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium iMinds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai 600036 Tamilnadu India Philips Research North America 345 Scarborough Road Briarcliff Manor NY 10510 USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo 152-8550 Japan Systems Biology C

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-rna recognition: A computational analysis of protein-rna complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：