14 NSFBIO:Bilateral BBSRC-NSF/BIO Collaborative Research: ABI Development: A Critical Assessment of Protein Function Annotation

14 NSFBIO:双边 BBSRC-NSF/BIO 合作研究:ABI 开发:蛋白质功能注释的批判性评估

基本信息

  • 批准号:
    BB/N004876/1
  • 负责人:
  • 金额:
    $ 44.58万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2015
  • 资助国家:
    英国
  • 起止时间:
    2015 至 无数据
  • 项目状态:
    已结题

项目摘要

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
目前GtR中并没有所有资助研究的摘要。这通常是因为在提交提案时不需要摘要,但也可能是因为摘要中包含个人详细信息等敏感信息。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
CAFA 挑战报告通过实验筛选改进了蛋白质功能预测和数百个基因的新功能注释
  • DOI:
    10.1101/653105
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhou N
  • 通讯作者:
    Zhou N
An expanded evaluation of protein function prediction methods shows an improvement in accuracy.
  • DOI:
    10.1186/s13059-016-1037-6
  • 发表时间:
    2016-09-07
  • 期刊:
  • 影响因子:
    12.3
  • 作者:
    Jiang Y;Oron TR;Clark WT;Bankapur AR;D'Andrea D;Lepore R;Funk CS;Kahanda I;Verspoor KM;Ben-Hur A;Koo da CE;Penfold-Brown D;Shasha D;Youngs N;Bonneau R;Lin A;Sahraeian SM;Martelli PL;Profiti G;Casadio R;Cao R;Zhong Z;Cheng J;Altenhoff A;Skunca N;Dessimoz C;Dogan T;Hakala K;Kaewphan S;Mehryary F;Salakoski T;Ginter F;Fang H;Smithers B;Oates M;Gough J;Törönen P;Koskinen P;Holm L;Chen CT;Hsu WL;Bryson K;Cozzetto D;Minneci F;Jones DT;Chapman S;Bkc D;Khan IK;Kihara D;Ofer D;Rappoport N;Stern A;Cibrian-Uhalte E;Denny P;Foulger RE;Hieta R;Legge D;Lovering RC;Magrane M;Melidoni AN;Mutowo-Meullenet P;Pichler K;Shypitsyna A;Li B;Zakeri P;ElShal S;Tranchevent LC;Das S;Dawson NL;Lee D;Lees JG;Sillitoe I;Bhat P;Nepusz T;Romero AE;Sasidharan R;Yang H;Paccanaro A;Gillis J;Sedeño-Cortés AE;Pavlidis P;Feng S;Cejuela JM;Goldberg T;Hamp T;Richter L;Salamov A;Gabaldon T;Marcet-Houben M;Supek F;Gong Q;Ning W;Zhou Y;Tian W;Falda M;Fontana P;Lavezzo E;Toppo S;Ferrari C;Giollo M;Piovesan D;Tosatto SC;Del Pozo A;Fernández JM;Maietta P;Valencia A;Tress ML;Benso A;Di Carlo S;Politano G;Savino A;Rehman HU;Re M;Mesiti M;Valentini G;Bargsten JW;van Dijk AD;Gemovic B;Glisic S;Perovic V;Veljkovic V;Veljkovic N;Almeida-E-Silva DC;Vencio RZ;Sharan M;Vogel J;Kansakar L;Zhang S;Vucetic S;Wang Z;Sternberg MJ;Wass MN;Huntley RP;Martin MJ;O'Donovan C;Robinson PN;Moreau Y;Tramontano A;Babbitt PC;Brenner SE;Linial M;Orengo CA;Rost B;Greene CS;Mooney SD;Friedberg I;Radivojac P
  • 通讯作者:
    Radivojac P
MOESM1 of The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
CAFA 挑战赛的 MOESM1 报告通过实验筛选改进了数百个基因的蛋白质功能预测和新功能注释
  • DOI:
    10.6084/m9.figshare.10458494
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhou N
  • 通讯作者:
    Zhou N
MOESM2 of The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
CAFA 挑战赛的 MOESM2 报告通过实验筛选改进了蛋白质功能预测和数百个基因的新功能注释
  • DOI:
    10.6084/m9.figshare.10458518
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhou N
  • 通讯作者:
    Zhou N
Prediction of Metabolic Pathway Involvement in Prokaryotic UniProtKB Data by Association Rule Mining.
  • DOI:
    10.1371/journal.pone.0158896
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Boudellioua I;Saidi R;Hoehndorf R;Martin MJ;Solovyev V
  • 通讯作者:
    Solovyev V
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Claire O'Donovan其他文献

Day-to-day variability in sleep and activity predict the onset of a hypomanic episode in patients with bipolar disorder
双相情感障碍患者睡眠和活动的日常变化可预测轻躁狂发作的开始
  • DOI:
    10.1016/j.jad.2025.01.026
  • 发表时间:
    2025-04-01
  • 期刊:
  • 影响因子:
    4.900
  • 作者:
    Abigail Ortiz;Ramzi Halabi;Martin Alda;Almendra Burgos;Alexandra DeShaw;Christina Gonzalez-Torres;Muhammad I. Husain;Claire O'Donovan;Mirkamal Tolend;Arend Hintze;Benoit H. Mulsant
  • 通讯作者:
    Benoit H. Mulsant
Glycosyltransferases in SWISS-PROT
  • DOI:
    10.1023/a:1006991121281
  • 发表时间:
    1998-01-01
  • 期刊:
  • 影响因子:
    3.100
  • 作者:
    Claire O'Donovan;Nicoletta Mitaritonna
  • 通讯作者:
    Nicoletta Mitaritonna
Categorical differentiation of the unipolar and bipolar disorders
  • DOI:
    10.1016/j.psychres.2021.113719
  • 发表时间:
    2021-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    Gordon Parker;Michael J. Spoelma;Gabriela Tavella;Martin Alda;Tomas Hajek;David L. Dunner;Claire O'Donovan;Janusz K. Rybakowski;Joseph F. Goldberg;Adam Bayes;Verinder Sharma;Philip Boyce;Vijaya Manicavasagar
  • 通讯作者:
    Vijaya Manicavasagar
15. Selection and Characterization of Digital Biomarkers of Depressive Episodes in Bipolar Disorder Using Explainable Machine Learning
15. 使用可解释机器学习对双相情感障碍抑郁发作的数字生物标志物进行选择和表征
  • DOI:
    10.1016/j.biopsych.2025.02.205
  • 发表时间:
    2025-05-01
  • 期刊:
  • 影响因子:
    9.000
  • 作者:
    Abigail Ortiz;Ramzi Halabi;Mirkamal Tolend;Arend Hintze;Alexandra De Shaw;Christina Gonzalez-Torres;Muhammad I. Husain;Claire O'Donovan;Daniel Blumberger;Martin Alda;Benoit H. Mulsant
  • 通讯作者:
    Benoit H. Mulsant
T28. COMPARISON OF QUANTITATIVE FAMILY HISTORY WITH POLYGENIC SCORES IN FAMILIES OF BIPOLAR PROBANDS
双相情感障碍先证者家庭中定量家系史与多基因评分的比较
  • DOI:
    10.1016/j.euroneuro.2023.08.315
  • 发表时间:
    2023-10-01
  • 期刊:
  • 影响因子:
    6.700
  • 作者:
    Evangelia Eirini Tsermpini;Katie Scott;Claire O'Donovan;Abraham Nunes;Martin Alda
  • 通讯作者:
    Martin Alda

Claire O'Donovan的其他文献

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{{ truncateString('Claire O'Donovan', 18)}}的其他基金

2020BBSRC-NSF/BIO: Linking Mass Spectrometry Computational Ecosystems to Enhance Biological Insights of Publicly-Available Data
2020BBSRC-NSF/BIO:连接质谱计算生态系统以增强对公开数据的生物学见解
  • 批准号:
    BB/W000156/1
  • 财政年份:
    2022
  • 资助金额:
    $ 44.58万
  • 项目类别:
    Research Grant
Standardised metabolite annotation workflows for enhancing biological interpretation in metabolomic data repositories
标准化代谢物注释工作流程,用于增强代谢组数据存储库中的生物学解释
  • 批准号:
    BB/T007389/1
  • 财政年份:
    2020
  • 资助金额:
    $ 44.58万
  • 项目类别:
    Research Grant

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