检索结果-内蒙古大学图书馆

Author Correction: Whole-genome sequencing of 1,171 elderly admixed individuals from Brazil

Nature communications 2022年第1期13卷 1831页

作者： Michel S Naslavsky Marilia O Scliar Guilherme L Yamamoto Jaqueline Yu Ting Wang Stepanka Zverinova Tatiana Karp Kelly Nunes José Ricardo Magliocco Ceroni Diego Lima de Carvalho Carlos Eduardo da Silva Simões Daniel Bozoklian Ricardo Nonaka Nayane Dos Santos Brito Silva Andreia da Silva Souza Heloísa de Souza Andrade Marília Rodrigues Silva Passos Camila Ferreira Bannwart Castro Celso T Mendes-Junior Rafael L V Mercuri Thiago L A Miller Jose Leonel Buzzo Fernanda O Rego Nathalia M Araújo Wagner C S Magalhães Regina Célia Mingroni-Netto Victor Borda Heinner Guio Carlos P Rojas Cesar Sanchez Omar Caceres Michael Dean Mauricio L Barreto Maria Fernanda Lima-Costa Bernardo L Horta Eduardo Tarazona-Santos Diogo Meyer Pedro A F Galante Victor Guryev Erick C Castelli Yeda A O Duarte Maria Rita Passos-Bueno Mayana Zatz Human Genome and Stem Cell Research Center University of São Paulo São Paulo SP Brazil. mnaslavsky@usp.br. Department of Genetics and Evolutionary Biology Biosciences Institute University of São Paulo São Paulo SP Brazil. mnaslavsky@usp.br. Hospital Israelita Albert Einstein São Paulo SP Brazil. mnaslavsky@usp.br. Human Genome and Stem Cell Research Center University of São Paulo São Paulo SP Brazil. Instituto da Criança Faculdade de Medicina da Universidade de São Paulo São Paulo SP Brazil. Orthopedic Research Labs Boston Children's Hospital and Department of Genetics Harvard Medical School Boston MA USA. Laboratório DASA São Paulo Brazil. Laboratory of Genome Structure and Ageing European Research Institute for the Biology of Ageing University Medical Center Groningen Groningen Netherlands. Department of Genetics and Evolutionary Biology Biosciences Institute University of São Paulo São Paulo SP Brazil. São Paulo State University (UNESP) Molecular Genetics and Bioinformatics Laboratory School of Medicine Botucatu State of São Paulo Brazil. São Paulo State University (UNESP) Department of Pathology School of Medicine Botucatu State of São Paulo Brazil. Departamento de Química Faculdade de Filosofia Ciências e Letras de Ribeirão Preto Universidade de São Paulo Ribeirão Preto São Paulo Brazil. Centro de Oncologia Molecular Hospital Sirio-Libanes São Paulo Brazil. Department of Biochemistry Institute of Chemistry University of São Paulo São Paulo São Paulo Brazil. Bioinformatics Graduate program University of São Paulo São Paulo Brazil. Departamento de Genética Ecologia e Evolução Instituto de Ciências Biológicas Universidade Federal de Minas Gerais Belo Horizonte MG Brazil. Núcleo de Ensino e Pesquisa Instituto Mário Penna Belo Horizonte MG Brazil. Laboratorio de Biotecnologia y Biologia Molecular Instituto Nacional de Salud Lima Peru. Universidad de Huánuco Huánuco Peru. Division of Cancer Epidemiology and Genetics National Cancer Insti

来源：评论

学校读者我要写书评

暂无评论

Nanopublications: A Growing Resource of Provenance-Centric Scientific Linked data

Nanopublications: A Growing Resource of Provenance-Centric S...

引用

IEEE International Conference on e-Science and Grid Computing

作者： Tobias Kuhn Albert Meroño-Peñuela Alexander Malic Jorrit H. Poelen Allen H. Hurlbert Emilio Centeno Ortiz Laura I. Furlong Núria Queralt-Rosinach Christine Chichester Juan M. Banda Egon Willighagen Friederike Ehrhart Chris Evelo Tareq B. Malas Michel Dumontier Department of Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands Vrije Universiteit Amsterdam Amsterdam Noord-Holland NL Institute of Data Science Maastricht University Netherlands 400 Perkins St Oakland California USA Department of Biology University of North Carolina Chapel Hill USA Research Programme on Biomedical Informatics Universitat Pompeu Fabra Barcelona Spain Department of Integrative Structural and Computational Biology The Scripps Research Institute La Jolla USA Datafair.xyz Geneva Switzerland Department of Computer Science Georgia State University USA Department of Bioinformatics BiGCaT NUTRIM Maastricht University The Netherlands Department of Human Genetics Leiden University Medical Center Netherlands

Nanopublications are a Linked data format for scholarly data publishing that has received considerable uptake in the last few years. In contrast to the common Linked data publishing practice, nanopublications work at the granular level of atomic information snippets and provide a consistent container format to attach provenance and metadata at this atomic level. While the nanopublications format is domain-independent, the datasets that have become available in this format are mostly from Life Science domains, including data about diseases, genes, proteins, drugs, biological pathways, and biotic interactions. More than 10 million such nanopublications have been published, which now form a valuable resource for studies on the domain level of the given Life Science domains as well as on the more technical levels of provenance modeling and heterogeneous Linked data. We provide here an overview of this combined nanopublication dataset, show the results of some overarching analyses, and describe how it can be accessed and queried.

关键词： Nanobioscience Diseases Linked data Proteins bioinformatics Publishing databases

来源：评论

学校读者我要写书评

暂无评论

Author Correction: The SEQC2 epigenomics quality control (EpiQC) study

引用

Genome biology 2021年第1期22卷 350页

作者： Jonathan Foox Jessica Nordlund Claudia Lalancette Ting Gong Michelle Lacey Samantha Lent Bradley W Langhorst V K Chaithanya Ponnaluri Louise Williams Karthik Ramaswamy Padmanabhan Raymond Cavalcante Anders Lundmark Daniel Butler Christopher Mozsary Justin Gurvitch John M Greally Masako Suzuki Mark Menor Masaki Nasu Alicia Alonso Caroline Sheridan Andreas Scherer Stephen Bruinsma Gosia Golda Agata Muszynska Paweł P Łabaj Matthew A Campbell Frank Wos Amanda Raine Ulrika Liljedahl Tomas Axelsson Charles Wang Zhong Chen Zhaowei Yang Jing Li Xiaopeng Yang Hongwei Wang Ari Melnick Shang Guo Alexander Blume Vedran Franke Inmaculada Ibanez de Caceres Carlos Rodriguez-Antolin Rocio Rosas Justin Wade Davis Jennifer Ishii Dalila B Megherbi Wenming Xiao Will Liao Joshua Xu Huixiao Hong Baitang Ning Weida Tong Altuna Akalin Yunliang Wang Youping Deng Christopher E Mason Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA. The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA. Department of Medical Sciences and Science for Life Laboratory Uppsala University Uppsala Sweden. EATRIS ERIC- European Infrastructure for Translational Medicine De Boelelaan 1118 1081 HZ Amsterdam The Netherlands. BRCF Epigenomics Core University of Michigan Medicine Ann Arbor MI 48109 USA. Department of Quantitative Health Sciences University of Hawaii John A. Burns School of Medicine Honolulu HI 96813 USA. Tulane University New Orleans LA 70118 USA. AbbVie Genomics Research Center 1 N. Waukegan Rd North Chicago IL 60036 USA. New England Biolabs Ipswich MA 01938 USA. Albert Einstein College of Medicine Bronx NY 10461 USA. Division of Hematology/Oncology Department of Medicine Epigenomics Core Facility Weill Cornell Medicine New York NY USA. Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland. Illumina Inc Madison WI 53705 USA. Faculty of Biochemistry Biophysics and Biotechnology Jagiellonian University Krakow Poland. Małopolska Centre of Biotechnology Jagiellonian University Krakow Poland. New York Genome Center New York NY 10013 USA. Center for Genomics School of Medicine Loma Linda University Loma Linda CA 92350 USA. Department of Allergy and Clinical Immunology State Key Laboratory of Respiratory Disease Guangzhou Institute of Respiratory Health the First Affiliated Hospital of Guangzhou Medical University Guangzhou Guangdong China. Department of Neurology The Second Affiliated Hospital of Zhengzhou University Zhengzhou 450014 China. Development of Medicine the University of Chicago Chicago IL 60637 USA. Department of Neurology the Second Affiliated Hospital of Zhengzhou University Zhengzhou 450014 China. Bioinformatics and Omics Data Science Platform Berlin Institute f

来源：评论

学校读者我要写书评

暂无评论

Correction: ColistinDose, a Mobile App for Determining Intravenous Dosage Regimens of Colistimethate in Critically Ill Adult Patients: Clinician-centered Design and Development Study

引用

JMIR mHealth and uHealth 2020年第12期8卷 e26593页

作者： Xueliang Hua Chen Li Jason M Pogue Varun S Sharma Ilias Karaiskos Keith S Kaye Brian T Tsuji Phillip J Bergen Yan Zhu Jiangning Song Jian Li Independent Researcher Santa Clara CA United States. Department of Biochemistry and Molecular Biology Monash University Melbourne Australia. Infection and Immunity Program Biomedicine Discovery Institute Monash University Melbourne Australia. Institute of Molecular Systems Biology Department of Biology ETH Zurich Zurich Switzerland. Department of Clinical Pharmacy University of Michigan College of Pharmacy Ann Arbor MI United States. 1st Internal Medicine and Infectious Diseases Department Hygeia Hospital Marousi Greece. Department of Internal Medicine University of Michigan Medical School Ann Arbor MI United States. Laboratory for Antimicrobial Dynamics NYS Center of Excellence in Bioinformatics & Life Sciences Buffalo NY United States. School of Pharmacy and Pharmaceutical Sciences University at Buffalo Buffalo NY United States. Department of Microbiology Monash University Melbourne Australia. Monash Centre for Data Science Faculty of Information Technology Monash University Melbourne Australia.

[This corrects the article DOI: 10.2196/20525.].

关键词：

来源：评论

学校读者我要写书评

暂无评论

Author Correction: COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms

引用

Scientific data 2020年第1期7卷 247页

作者： Marek Ostaszewski Alexander Mazein Marc E Gillespie Inna Kuperstein Anna Niarakis Henning Hermjakob Alexander R Pico Egon L Willighagen Chris T Evelo Jan Hasenauer Falk Schreiber Andreas Dräger Emek Demir Olaf Wolkenhauer Laura I Furlong Emmanuel Barillot Joaquin Dopazo Aurelio Orta-Resendiz Francesco Messina Alfonso Valencia Akira Funahashi Hiroaki Kitano Charles Auffray Rudi Balling Reinhard Schneider Luxembourg Centre for Systems Biomedicine University of Luxembourg Belvaux Luxembourg. European Institute for Systems Biology and Medicine (EISBM) Vourles France. Ontario Institute for Cancer Research Toronto Canada. College of Pharmacy and Health Sciences St. John's University Queens NY USA. Institut Curie PSL Research University Mines Paris Tech Inserm Paris France. Department of Biology Univ. Évry University of Paris-Saclay Genopole 91025 Évry France. European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Hinxton UK. Institute of Data Science and Biotechnology Gladstone Institutes San Francisco United States. Department of Bioinformatics-BiGCaT NUTRIM Maastricht University Maastricht The Netherlands. Maastricht Centre for Systems Biology Maastricht University Maastricht The Netherlands. Helmholtz Zentrum München Institute of Computational Biology Neuherberg Germany. Center for Mathematics Technische Universität München Garching Germany. Faculty of Mathematics and Natural Sciences University of Bonn Bonn Germany. University of Konstanz Department of Computer and Information Science Konstanz Germany. Monash University Faculty of Information Technology Melbourne Australia. Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens Institute for Bioinformatics and Medical Informatics (IBMI) University of Tübingen 72076 Tübingen Germany. Department of Computer Science University of Tübingen 72076 Tübingen Germany. German Center for Infection Research (DZIF) partner site Tübingen Germany. Department of Molecular and Medical Genetics School of Medicine Oregon Health & Science University Portland USA. Department of Systems Biology & Bioinformatics University of Rostock Rostock Germany. Stellenbosch Institute of Advanced Study (STIAS) Wallenberg Research Centre at Stellenbosch University 7602 Stellenbosch South Africa. Research Programme on Biomedical informatics Hospital del Mar Medical Research

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

关键词：

来源：评论

学校读者我要写书评

暂无评论

Crowdsourcing annotation system of object counting dataset for deep learning algorithm

引用

IOP Conference Series: Earth and Environmental Science 2018年第1期195卷

作者： Tjeng Wawan Cenggoro Fidelson Tanzil Ayu Hidayah Aslamiah Ettikan Kandasamy Karuppiah Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 NVIDIA Corporation Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Deep Learning is currently the state-of-the-art technique for various Computer Vision tasks, including object counting. Despite of its high performance, Deep Learning requires a gigantic amount of training data to show its best result. Getting this massive data in reasonable time requires a proper strategy such as crowdsourcing. However, in case of object counting, we found no crowdsourcing system able to effectively collect necessary data. To tackle this problem, we develop a crowdsourcing system to annotate image for object counting dataset. This system is also equipped with validation system to ensure the quality of collected dataset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Use of the total cancer care system to enrich screening for cd30-positive solid tumors for patient enrollment into a brentuximab vedotin clinical trial: A pilot study to evaluate feasibility

引用

JMIR Research Protocols 2017年第3期6卷 e45页

作者： Li, Bin Eschrich, Steven A. Berglund, Anders Mitchell, Melissa Fenstermacher, David Danaee, Hadi Dai, Hongyue Sullivan, Daniel Trepicchio, William L. Dalton, William S. Takeda Pharmaceuticals International Company Takeda Data Science Institute Cambridge MA United States H Lee Moffitt Cancer Center and Research Institute Biostatistics and Bioinformatics Tampa FL United States M2Gen Administration Tampa FL United States MedImmune LLC Research Bioinformatics Gaithersburg MD United States Takeda Pharmaceuticals International Company Translational and Biomarker Research Cambridge MA United States M2Gen Bioinformatics Tampa FL United States H Lee Moffitt Cancer Center and Research Institute Blood and Marrow Transplantation Tampa FL United States

Background: One approach to identify patients who meet specific eligibility criteria for target-based clinical trials is to use patient and tumor registries to prescreen patient populations. Objective: Here we demonstrate that the Total Cancer Care (TCC) Protocol, an ongoing, observational study, may provide a solution for rapidly identifying patients with CD30-positive tumors eligible for CD30-targeted therapies such as brentuximab vedotin. Methods: The TCC patient gene expression profiling database was retrospectively screened for CD30 gene expression determined using HuRSTA-2a520709 Affymetrix arrays (GPL15048). Banked tumor tissue samples were used to determine CD30 protein expression by semiquantitative immunohistochemistry. Statistical comparisons of Z- and H-scores were performed using R statistical software (The R Foundation), and the predictive value, accuracy, sensitivity, and specificity of CD30 gene expression versus protein expression was estimated. Results: As of March 2015, 120,887 patients have consented to the institutional review board-approved TCC Protocol. A total of 39,157 fresh frozen tumor specimens have been collected, from which over 14,000 samples have gene expression data available. CD30 RNA was expressed in a number of solid tumors;the highest median CD30 RNA expression was observed in primary tumors from lymph node, soft tissue (many sarcomas), lung, skin, and esophagus (median Z-scores 1.011, 0.399, 0.202, 0.152, and 1.011, respectively). High level CD30 gene expression significantly enriches for CD30-positive protein expression in breast, lung, skin, and ovarian cancer;accuracy ranged from 72% to 79%, sensitivity from 75% to 100%, specificity from 70% to 76%, positive predictive value from 20% to 40%, and negative predictive value from 95% to 100%. Conclusions: The TCC gene expression profiling database guided tissue selection that enriched for CD30 protein expression in a number of solid tumor types. Such an approach may improve scree

关键词： Antitumor agents CD30 antigen Clinical trial database management systems Medical oncology

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to "Dissecting the genetic heterogeneity of gastric cancer"

引用

EBioMedicine 2023年 94卷 104709页

作者： Timo Hess Carlo Maj Jan Gehlen Oleg Borisov Stephan L Haas Ines Gockel Michael Vieth Guillaume Piessen Hakan Alakus Yogesh Vashist Carina Pereira Michael Knapp Vitalia Schüller Alexander Quaas Heike I Grabsch Jessica Trautmann Ewa Malecka-Wojciesko Anna Mokrowiecka Jan Speller Andreas Mayr Julia Schröder Axel M Hillmer Dominik Heider Florian Lordick Ángeles Pérez-Aísa Rafael Campo Jesús Espinel Fernando Geijo Concha Thomson Luis Bujanda Federico Sopeña Ángel Lanas María Pellisé Claudia Pauligk Thorsten Oliver Goetze Carolin Zelck Julian Reingruber Emadeldin Hassanin Peter Elbe Sandra Alsabeah Mats Lindblad Magnus Nilsson Nicole Kreuser René Thieme Francesca Tavano Roberta Pastorino Dario Arzani Roberto Persiani Jin-On Jung Henrik Nienhüser Katja Ott Ralf R Schumann Oliver Kumpf Susen Burock Volker Arndt Anna Jakubowska Małgorzta Ławniczak Victor Moreno Vicente Martín Manolis Kogevinas Marina Pollán Justyna Dąbrowska Antonio Salas Olivier Cussenot Anne Boland-Auge Delphine Daian Jean-Francois Deleuze Erika Salvi Maris Teder-Laving Gianluca Tomasello Margherita Ratti Chiara Senti Valli De Re Agostino Steffan Arnulf H Hölscher Katharina Messerle Christiane Josephine Bruns Armands Sīviņš Inga Bogdanova Jurgita Skieceviciene Justina Arstikyte Markus Moehler Hauke Lang Peter P Grimminger Martin Kruschewski Nikolaos Vassos Claus Schildberg Philipp Lingohr Karsten Ridwelski Hans Lippert Nadine Fricker Peter Krawitz Per Hoffmann Markus M Nöthen Lothar Veits Jakob R Izbicki Adrianna Mostowska Federico Martinón-Torres Daniele Cusi Rolf Adolfsson Geraldine Cancel-Tassin Aksana Höblinger Ernst Rodermann Monika Ludwig Gisela Keller Andres Metspalu Hermann Brenner Joerg Heller Markus Neef Michael Schepke Franz Ludwig Dumoulin Lutz Hamann Renato Cannizzaro Michele Ghidini Dominik Plaßmann Michael Geppert Peter Malfertheiner Olivier Glehen Tomasz Skoczylas Marek Majewski Jan Lubiński Orazio Palmieri Stefania Boccia Anna Latiano Nuria Aragones Thomas Schmidt Mário Dinis-Ribeiro Rui Medeiros Salah-Eddin Al-Batran Mārcis Leja Juozas Institute of Human Genetics University of Marburg Marburg Germany Institute of Human Genetics University of Bonn School of Medicine & University Hospital Bonn Bonn Germany. Institute for Genomic Statistics and Bioinformatics Medical Faculty University of Bonn Bonn Germany. Institute of Human Genetics University of Marburg Marburg Germany. Department of Upper GI Diseases Karolinska University Hospital and Unit of Gastroenterology and Rheumatology Karolinska Institutet Stockholm Sweden. Department of Visceral Transplant Thoracic and Vascular Surgery University Hospital Leipzig Leipzig Germany. Institute for Pathology Friedrich-Alexander-University Erlangen-Nuernberg Klinikum Bayreuth Bayreuth Germany. Department of Digestive and Oncological Surgery Claude Huriez Hospital CHU Lille Lille France. Department of General Visceral Cancer and Transplant Surgery University of Cologne Cologne Germany. Department of General Visceral and Thoracic Surgery University Medical Center Hamburg-Eppendorf University of Hamburg Hamburg Germany Centre for Surgical Oncology Medias Klinikum Burghausen Burghausen Germany. Molecular Oncology and Viral Pathology Group IPO Porto Research Center (CI-IPOP) Portuguese Institute of Oncology of Porto (IPO Porto) 4200-072 Porto Portugal Porto Comprehensive Cancer Center & RISE @ CI-IPO University of Porto 4200-450 Porto Portugal. Institute of Medical Biometrics Informatics and Epidemiology (IMBIE) Medical Faculty University of Bonn Bonn Germany. Institute of Pathology University Hospital Cologne Medical Faculty University of Cologne Germany. Department of Pathology GROW School for Oncology and Developmental Biology Maastricht University Medical Center Maastricht the Netherlands Pathology and Data Analytics Leeds Institute of Medical Research at St James's University of Leeds Leeds United Kingdom. Department of Digestive Tract Diseases Medical University of Lodz Lodz Poland. Department of Mathematics and Computer Science Unive

来源：评论

学校读者我要写书评

暂无评论

Highly accurate model for prediction of lung nodule malignancy with ct scans

arXiv

引用

arXiv 2018年

作者： Causey, Jason Zhang, Junyu Ma, Shiqian Jiang, Bo Qualls, Jake Politte, David G. Prior, Fred Zhang, Shuzhong Huang, Xiuzhen Department of Computer Science Arkansas State University JonesboroAR72467 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin N.T. Hong Kong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Mallinckrodt Institute of Radiology Washington University St. LouisMO63110 United States Department of Biomedical Informatics University of Arkansas for Medical Sciences Little RockAR72205 United States UALR/UAMS Joint Graduate Program in Bioinformatics Little RockAR72204 United States

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://***/NoduleX. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

A second update on mapping the human genetic architecture of COVID-19

引用

Nature 2023年第7977期621卷 E7-E26页

作者： Masahiro Kanai Christine Stevens Benjamin M. Neale Mark Daly Andrea Ganna Amy Trankiem Mary K. Balaconis Samuli Ripatti Lindo Nkambul Mark J. Daly Sam Bryant Matthew Solomonson Shea J. Andrews Mattia Cordioli Juha Karjalainen Juha Mehtonen Matti Pirinen Andrea Corbetta Bradley Jermy Kati Donner Katja Kivinen Aarno Palotie Mari Kaunisto Kumar Veerapen Konrad J. Karczewski Alicia R. Martin Elizabeth G. Atkinson Kristin Tsuo Nikolas Baya Rahul Gupta Raymond K. Walters Duncan S. Palmer Gopal Sarma Nathan Cheng Wenhan Lu Claire Churchhouse Jacqueline I. Goldstein Daniel King Wei Zhou Cotton Seed Hilary Finucane F. Kyle Satterstrom Gita A. Pathak Akiko Iwasaki Karolina Chwialkowska Karolina Chwiałkowska Brooke N. Wolford Hajar Fauzan Ahmad Shea Andrews Kathrin Aprile von Hohenstaufen Puoti Palwende R. Boua Guillaume Butler-Laporte Celia M. T. Greenwood Bartha M. Knoppers Mark Lathrop Carmen L. Cadilla Francesca Colombo Nicole Dueker Chloe Kirk Atanu Kumar Dutta Yasser M. El-Sherbiny Jehan J. El-Jawhari Doaa Shahin Ahmed Elzeiny Tamer A. Mansour Madonna M. Eltoukhy Attia A. S. Mohamed Sahar Esmaeeli Annika Faucon Israel Fernández Cadenas Israel Fernandez-Cadenas Laia Llucià-Carol Natalia Cullell Elena Muiño Jara Cárcel-Márquez Margherita Francescatto Laurent Francioli Lindokuhle Nkambule Jatin Arora Soumya Raychaudhuri Caroline Cusick Lude Franke Macarena Fuentes Macarena Fuentes-Guajardo David Gómez Cabrero Emi N. Harry Philip Jansen József L. Szentpéteri Réka Várnai Elżbieta Kaja Athanasios Kousathanas Dorote Pasko Mark J. Caulfield Alex Stuckey Christopher A. Odhams Susan Walker Daniel Rhodes Richard H. Scott Loukas Moutsianas Afshan Siddiq Peter Goddard Sally Donovan Tala Zainy Fiona Maleady-Crowe Linda Todd Shahla Salehi Greg Elgar Georgia Chan Prabhu Arumugam Christine Patch Augusto Rendon Tom A. Fowler Jose E. Krieger Sanjay K. Patel Audrey Lemaçon Sophie Limou Pietro Lió Eirini Marouli Charles Hinds Minttu M. Marttila Carolina Medina-Gómez Isabelle Migeotte Soumyajit Mondal Andrés Moreno-Estrada Leire Moya Tomok Broad Institute of MIT and Harvard Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland Public Health Faculty of Medicine University of Helsinki Helsinki Finland Analytic & Translational Genetics Unit Massachusetts General Hospital Boston MA USA Stanley Center for Psychiatric Research & Program in Medical and Population Genetics Cambridge UK Institute for Molecular Medicine Finland (FIMM) Univerisity of Helsinki Helsinki Finland University of California San Francisco San Francisco CA USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Department of Psychiatry School of Medicine Yale University New Haven CT USA Veteran Affairs Connecticut Healthcare System West Haven CT USA Yale University New Haven CT USA Centre for Bioinformatics and Data Analysis Medical University of Bialystok Bialystok Poland Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA Faculty of Industrial Sciences and Technology Universiti Malaysia Pahang Pahang Malaysia Icahn School of Medicine at Mount Sinai New York NY USA Genolier Innovation Network and Hub Swiss Medical Network Genolier Healthcare Campus Genolier Switzerland Immediate Independent Multidisciplinary Med & Biotech Research Association Milan Italy Clinical Research Unit of Nanor

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：