检索结果-内蒙古大学图书馆

Author Correction: Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

引用

Nature genetics 2018年第12期50卷 1754页

作者： Huipeng Li Elise T Courtois Debarka Sengupta Yuliana Tan Kok Hao Chen Jolene Jie Lin Goh Say Li Kong Clarinda Chua Lim Kiat Hon Wah Siew Tan Mark Wong Igor Cima Min-Han Tan Lawrence J K Wee Axel M Hillmer Iain Beehuat Tan Paul Robson Shyam Prabhakar Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India. Synthetic Biology Genome Institute of Singapore Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. Department of Pathology Singapore General Hospital Singapore Singapore. Department of Colorectal Surgery Singapore General Hospital Singapore Singapore. Institute of Bioengineering and Nanotechnology Singapore Singapore. Data Analytics Department Institute for Infocomm Research Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. paul.robson@***. The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA. paul.robson@***. Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA. paul.robson@***. Department of Biological Sciences National University of Singapore Singapore Singapore. paul.robson@***. Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. prabhakars@gis.a-star.edu.sg.

In the version of the article published, the author list is not accurate. Igor Cima and Min-Han Tan should have been authors, appearing after Mark Wong in the author list, while Paul Jongjoon Choi should not have been listed as an author. Igor Cima and Min-Han Tan both have the affiliation Institute of Bioengineering and Nanotechnology, Singapore, Singapore, and their contributions should have been noted in the Author Contributions section as "I.C. preprocessed Primary Cell Atlas data with inputs from M.-H.T." The following description of the contribution of Paul Jongjoon Choi should not have appeared: "P.J.C. supported the smFISH experiments." In the 'RCA: global panel' section of the Online Methods, the following sentence should have appeared as the second sentence, "An expression atlas of human primary cells (the Primary Cell Atlas) was preprocessed similarly to in ref. 55," with new reference 55 (Cima, I. et al. Tumor-derived circulating endothelial cell clusters in colorectal cancer. science Transl. Med. 8, 345ra89, 2016).

关键词：

来源：评论

学校读者我要写书评

暂无评论

Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

引用

The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

关键词：

来源：评论

学校读者我要写书评

暂无评论

Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18: a modelling study

引用

The Lancet HIV 2021年第6期8卷 e363-e375页

作者： Sartorius, Benn VanderHeide, John D. Yang, Mingyou Goosmann, Erik A. Hon, Julia Haeuser, Emily Cork, Michael A. Perkins, Samantha Jahagirdar, Deepa Schaeffer, Lauren E. Serfes, Audrey L. LeGrand, Kate E. Abbastabar, Hedayat Abebo, Zeleke Hailemariam Abosetugn, Akine Eshete Abu-Gharbieh, Eman Accrombessi, Manfred Mario Kokou Adebayo, Oladimeji M. Adegbosin, Adeyinka Emmanuel Adekanmbi, Victor Adetokunboh, Olatunji O. Adeyinka, Daniel Adedayo Ahinkorah, Bright Opoku Ahmadi, Keivan Ahmed, Muktar Beshir Akalu, Yonas Akinyemi, Oluwaseun Oladapo Akinyemi, Rufus Olusola Aklilu, Addis Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Noore Alamneh, Alehegn Aderaw Alanzi, Turki M. Alemu, Biresaw Wassihun Alhassan, Robert Kaba Ali, Tilahun Alipour, Vahid Amini, Saeed Ancuceanu, Robert Ansari, Fereshteh Anteneh, Zelalem Alamrew Anvari, Davood Anwer, Razique Appiah, Seth Christopher Yaw Arabloo, Jalal Asemahagn, Mulusew A. Asghari Jafarabadi, Mohammad Asmare, Wondwossen Niguse Atnafu, Desta Debalkie Atout, Maha Moh'd Wahbi Atreya, Alok Ausloos, Marcel Awedew, Atalel Fentahun Ayala Quintanilla, Beatriz Paulina Ayanore, Martin Amogre Aynalem, Yared Asmare Ayza, Muluken Altaye Azari, Samad Azene, Zelalem Nigussie Babar, Zaheer-Ud-Din Baig, Atif Amin Balakrishnan, Senthilkumar Banach, Maciej Bärnighausen, Till Winfried Basu, Sanjay Bayati, Mohsen Bedi, Neeraj Bekuma, Tariku Tesfaye Bezabhe, Woldesellassie M. Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Pankaj Bhattacharyya, Krittika Bhutta, Zulfiqar A. Bibi, Sadia Bikbov, Boris Birhan, Tsegaye Adane Bitew, Zebenay Workneh Bockarie, Moses John Boloor, Archith Brady, Oliver J. Bragazzi, Nicola Luigi Briko, Andrey Nikolaevich Briko, Nikolay Ivanovich Burugina Nagaraja, Sharath Butt, Zahid A. Cárdenas, Rosario Carvalho, Felix Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Chowdhury, Mohiuddin Ahsanul Kabir Chu, Dinh-Toi Cook, Aubrey J. Cormier, Natalie Maria Cowden, Richard G. Culquichicon, Carlos Dagnew, Baye Dahlawi, Saad M.A. D Centre for Tropical Medicine and Global Health Nuffield Department of Medicine University of Oxford Oxford United Kingdom Malaria Atlas Project University of Oxford Oxford United Kingdom The George Institute for Global Health University of Oxford Oxford United Kingdom Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Insights Program Bill and Melinda Gates Foundation Seattle WA United States Global Programs Medical Teams International Seattle WA United States Department of Pediatric Newborn Medicine Brigham and Women's Hospital Boston MA United States Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Pediatric Chronic Kidney Disease Research Center Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Public Health Arba Minch University Arba Minch Ethiopia Department of Medical Laboratory Sciences Arba Minch University Arba Minch Ethiopia College of Medicine and Health Science Arba Minch University Arba Minch Ethiopia Department of Nursing Arba Minch University Arba Minch Ethiopia Department of Biomedical Sciences Arba Minch University Arba Minch Ethiopia Department of Public Health Debre Berhan University Debre Brehan

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676·5 (513·6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique,

关键词：

来源：评论

学校读者我要写书评

暂无评论

The impact of climate change on global wheat production

The impact of climate change on global wheat production

引用

第七届国际作物科学大会

作者： S.Asseng P.Martre A.Maiorano R.P.Rtter G.O'Leary G.Fitzgerald C.Girousse M.A.Baber M.P.Reynolds A.M.S.Kheir P.J.Thorburn K.Waha A.C.Ruane P.K.Aggarwal M.Ahmed J.Balkovic B.Basso A.Berger C.Biernath M.Bindi D.Cammarano A.J.Challinor G.De Sanctis J.Doltra B.Dumont E.Eyshi Rezaei E.Fereres R.Ferrise M.Garcia-Vila S.Gayler G.Hoogenboom R.C.Izaurralde M.Jabloun C.D.Jones B.T.Kassie K.C.Kersebaum C.Klein A.K.Koehler B.Liu S.Minoli M.Montesino San Martin C.Muller S.Naresh Kumar C.Nendel J.E.Olesen T.Palosuo J.R.Porter E.Priesack D.Ripoche M.A.Semenov C.Stockle P.Stratonovitch T.Streck I.Supit F.Tao M.Van der Velde D.Wallach E.Wang H.Webber J.Wolf P.Woli Z.Zhang Y.Zhu F.Ewert Agricultural & Biological Engineering Department University of Florida UMR GDEC INRAUniversite Blaise Pascal World Food Crops Breeding(wheat & oat) 3105 McCarty Hall BDepartment of AgronomyIFASUniversity of Florida CIMMYT Int.Adpo D.F.Mexico CSIRO Agriculture Flagship CSIRO Queensland Biosci Precinct St Lucia CGIAR Research Program on Climate Change Agriculture and Food SecurityInternational Water Management Institute Biological Systems Engineering Washington State University Department of agronomy PMAS Arid Agriculture University Comenius University Faculty of Natural ScienceDepartment of Soil Science Department of Geological Sciences Michigan State University W.K.Kellogg Biological Station Michigan State University Department of Agri-food Production and Environmental Sciences(DISPAA) University of Florence Institute for Climate and Atmospheric Science School of Earth and EnvironmentUniversity of Leeds CGIAR-ESSP Program on Climate Change Agriculture and Food SecurityInternational Centre for Tropical Agriculture(CIAT) Institute of Crop Science and Resource Conservation INRES University of Bonn IAS-CSIC and University of Cordoba Institute of Soil Science and Land Evaluation University of Hohenheim Department of Geographical Sciences University of Maryland Texas A&M AgriLife Research and Extension Center Texas A&M University Department of Agroecology Aarhus University Institute of Biochemical Plant Pathology Helmholtz Zentrum Munchen-German Research Center for Environmental Health College of Agriculture Nanjing Agricultural University Potsdam Institute for Climate Impact Research University of Copenhagen Department of Plant & Environmental Science Centre for Environment Science and Climate Resilient Agriculture Indian Agricultural Research InstituteIARI PUSA University of Greenwich Natural Resources Institute INRA US1116 AgroClim Computational and Systems Biology Department Rothamsted Research Plant Production Systems & Earth System Science Wageningen University Institute of Geographical Sciences and Natu

The Agricultural Model Intercomparison and Improvement Project has shown that many wheat crop models can simulate grain yields and growth dynamics under a range of growing conditions,but simulation results often *** model uncertainties increase with higher temperatures and with combined increased temperature and CO,however,multi-model ensemble medians have proven with field observations to be a good predictor of observed data under various growing *** multi-model ensemble median simulations showed that global wheat production declines by 6% for each degree of global temperature *** simulated impact is similar to temperature impact assessments using statistical regression methods with aggregated farm *** on the temperature impact study,new simulations of increased temperature were combined with elevated CO and rainfall changes to assess their impact on yield and protein and included the possible role of genetic adaptations to climate change at local,regional and global scales.

关键词： Global foods security Climate change Adaptation Wheat

来源：评论

学校读者我要写书评

暂无评论

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

引用

NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

来源：评论

学校读者我要写书评

暂无评论

Using PepExplorer to Filter and Organize De Novo Peptide Sequencing Results

引用

Current Protocols in Bioinformatics 2015年第1期51卷 13.27.1-13.27.9页

作者： da Veiga Leprevost, Felipe Barbosa, Valmir C. Carvalho, Paulo Costa Computational Mass Spectrometry Group Carlos Chagas Institute–Fiocruz. Curitiba Paraná Brazil Department of Pathology University of Michigan Ann Arbor United States Systems Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

PepExplorer aids in the biological interpretation of de novo sequencing results;this is accomplished by assembling a list of homolog proteins obtained by aligning results from widely adopted de novo sequencing tools against a target-decoy sequence database. Our tool relies on pattern recognition to ensure that the results satisfy a user-given false-discovery rate (FDR). For this, it employs a radial basis function neural network that considers the precursor charge states, de novo sequencing scores, the peptide lengths, and alignment scores. PepExplorer is recommended for studies addressing organisms with no genomic sequence available. PepExplorer is integrated into the PatternLab for proteomics environment, which makes available various tools for downstream data analysis, including the resources for quantitative and differential proteomics. © 2015 by John Wiley & Sons, Inc. © 2015 John Wiley & Sons, Inc.

关键词： de novo sequencing mass spectrometry proteomics

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: A Multi-Institutional Comparison of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameter Calculations

引用

Scientific reports 2018年第1期8卷 4422页

作者： Rachel B. Ger Xenia J. Fave Heng Li Jihong Wang Rebecca M. Howell Laurence E. Court James A. Bankson R. Jason Stafford John D. Hazle Clifton D. Fuller Abdallah S. R. Mohamed Hesham Elhalawani Caroline Chung Steven J. Frank Musaddiq J. Awan Yao Ding Kelsey B. Mathieu Kimberly Li Wei Huang Andrew L. Beers Jayashree Kalpathy-Cramer Brandon Driscoll Catherine Coolens David A. Hormuth II Thomas E. Yankeelov Petra J. van Houdt Uulke A. van der Heide Renjie He Shouhao Zhou Vlad C. Sandulache Stephen Y. Lai Daniel P. Barboriak Department of Radiation Physics The University of Texas MD Anderson Cancer Center Houston Texas USA The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Houston Texas USA Department of Imaging Physics The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Radiation Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Clinical Oncology and Nuclear Medicine Faculty of Medicine University of Alexandria Alexandria Egypt Techna Institute University Health Network Toronto Ontario Canada Case Western Reserve University Cleveland OH USA University Hospitals Cleveland OH USA Advanced Imaging Research Center Knight Cancer Institute Oregon Health & Science University Portland Oregon USA The International School of Beaverton Beaverton Oregon USA Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital/Division of Health Sciences & Technology Massachusetts Institute of Technology Charlestown Massachusetts USA Radiation Medicine Program Princess Margaret Cancer Centre University Health Network Toronto Ontario Canada Department of Radiation Oncology University of Toronto Toronto Ontario Canada Institute for Computational Engineering and Sciences The University of Texas Austin Texas USA Department of Radiation Oncology The Netherlands Cancer Institute Amsterdam The Netherlands United Imaging Healthcare America Houston Texas USA Department of Biostatistics The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Otolaryngology Head and Neck Surgery Baylor College of Medicine Houston Texas USA Department of Head and Neck Surgery The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Molecular and Cellular Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Radiology Duke University Medical Center Durham North Carolina USA

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Erratum to: The real cost of sequencing: scaling computation to keep pace with data generation

引用

Genome biology 2016年第1期17卷 78页

作者： Paul Muir Shantao Li Shaoke Lou Daifeng Wang Daniel J Spakowicz Leonidas Salichos Jing Zhang George M Weinstock Farren Isaacs Joel Rozowsky Mark Gerstein Department of Molecular Cellular and Developmental Biology Yale University New Haven CT 06520 USA. Systems Biology Institute Yale University West Haven CT 06516 USA. Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. The Jackson Laboratory for Genomic Medicine Farmington CT 06032 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. mark@***. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. mark@***. Department of Computer Science Yale University New Haven CT 06520 USA. mark@***.

来源：评论

学校读者我要写书评

暂无评论

Author Correction: A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

引用

Nature communications 2019年第1期10卷 2956页

作者： Lohith Madireddy Kicheol Kim Xiaoming Jia Adam Santaniello Stacy J. Caillier Bruce A. C. Cree Roland Henry Stephen L. Hauser Jorge R. Oksenberg Sergio E. Baranzini Nikolaos A. Patsopoulos Philip De Jager Chris Cotsapas Matthew R. Lincoln David A. Hafler Steffan D. Bos Hanne F. Harbo Tone Berge Elisabeth G. Celius Ashley Beecham Jacob McCauley Margaret A. Pericak-Vance Till F. M. Andlauer Christiane Gasperi Bernhard Hemmer Lisa F. Barcellos Luisa Bernardinelli Filippo Martinelli-Boneschi David R. Booth Graeme J. Stewart Farren Briggs Jonathan Haines Manuel Comabella Giancarlo Comi Federica Esposito Sandra D’Alfonso Katrina Dedham Pierre Duquette Efthimios Dardiotis Bertrand Fontaine An Goris Bénédicte Dubois Pierre-Antoine Gourraud Georgios Hadjigeorgiou Clive Hawkins Seema Kalra Rogier Hintzen Dana Horakova Noriko Isobe Jun-ichi Kira Michael Khalil Ingrid Kockum Tomas Olsson Christina M. Lill Felix Luessi Frauke Zipp Roland Martin Annette Oturai Aarno Palotie Janna Saarela Adrian Ivinson Bruce V. Taylor Alastair Compston Stephen Sawcer Weill Institute for Neurosciences Department of Neurology University of California San Francisco San Francisco CA 94158 USA Bakar Institute for Computational Health Science. University of California San Francisco San Francisco CA 94158 USA Systems Biology and Computer Science Program Ann Romney Center for Neurological Diseases Department of Neurology and Division of Genetics Department of Medicine Brigham & Women’s Hospital Harvard Medical School Boston MA 02115 USA Broad Institute of Harvard University and Massachusetts Institute of Technology Cambridge MA 02142 USA Department of Neurology Center for Translational and Computational Neuroimmunology and Multiple Sclerosis Center Columbia University Medical Center New York NY 10032 USA Departments of Neurology Yale School of Medicine 300 George St New Haven CT 06511 USA Department of Genetics Yale School of Medicine 300 George St New Haven CT 06511 USA Institute of Clinical Medicine University of Oslo Oslo 0318 Norway Department of Neurology Oslo University Hospital Oslo 0424 Norway Department of Mechanical Electronics and Chemical Engineering Oslo Metropolitan University Oslo 0167 Norway Institute of Health and Society University of Oslo Oslo 0318 Norway John P. Hussman Institute for Human Genomics University of Miami Miller School of Medicine Miami FL 33136 USA Dr. John T. Macdonald Foundation Department of Human Genetics University of Miami Miller School of Medicine Miami FL 33136 USA Department of Neurology Klinikum rechts der Isar School of Medicine Technical University of Munich 81675 Munich Germany Munich Cluster for Systems Neurology (SyNergy) 81377 Munich Germany Division of Epidemiology School of Public HealthUniversity of California 324 Stanley Hall MC#3220 Berkeley CA 94720 USA Section of Biostatistics Neurophyisiology and Psychiatry Unit of medical and genomic statistics Universita of Pavia Pavia 27100 Italy Department of Biomedical Sciences for Health Univers

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

A node placement optimization method for watershed underwater sensor networks 9

A node placement optimization method for watershed underwate...

引用

9th ACM International Conference on Underwater Networks and Systems, WUWNet 2014

作者： Barbosa, Gentil V. Letouze, Patrick Xavier, Adilson E. Department of Computer Science UFT - Universidade Federal do Tocantins PESC Brazil Department of Computer Science UFT - Universidade Federal do Tocantins MCS - Postgraduate Program of System's Computational Modeling Brazil PESC - Postgraduate Program of System's Engineering and Computation UFRJ - Universidade Federal do Rio de Janeiro Brazil

ISBN: (纸本)9781450332774

Given a set of underwater sensors coordinates that are usually determined by a specialist for the design of a watershed monitoring system, where should be placed the sinks and the base station? The answer may be the minimization of the Variable Internode Distance. In such cases, a two dimensional architecture is acceptable because it is a shallow water system. Hence, in this paper, it is proposed a two-level node distance minimization for Underwater Wireless Sensor Network for monitoring systems. The mathematical method employed for optimization is the Hyperbolic Smoothing approach and the proposed method includes the placement of the base-station in the algorithm. Copyright 2014 ACM.

关键词： Base stations

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：