课题基金 / 基金详情

项目摘要

项目成果

Steven E Brenner的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Genomic data hold the promise of revolutionizing our understanding and treatment of human disease. Multiple barriers stand between the acquisition of the data and realizing these and other benefits. Rapid accumulation of genomic data far exceeds our capacity to reliably interpret genomic variation. New developments in artificial intelligence and machine learning, combined with increased computing power and domain knowledge, provide hope for the deployment of enhanced computational tools in both basic research and clinical practice. Use of these methods critically depends upon reliable characterization of their performance. The Center for Critical Assessment of Genome Interpretation (C-CAGI) will address these needs, through objective evaluation of the state of the art in relating human genetic variation and health. CAGI has had five editions since 2010 with 50 challenges posed to the community taken on by hundreds of predictors, leading to scores of publications about prediction methods and their assessment. We propose for C-CAGI to continue to advance the field of variant interpretation through the following Specific Aims: 1. Develop community experiments to evaluate the quality of computational methods for interpreting genomic variation data. C-CAGI will conduct community experiments in which participants make bona fide blinded predictions of disease related phenotypes on the basis of genomic data. We will engage a diverse predictor community to spur innovation. The CAGI Ethics Forum will vet studies to ensure that privacy and sharing maintain the highest standards and will educate the community. 2. Assess the quality of current computational methods for interpreting genomic variation data; highlight innovations and progress at interactive conferences. Predictions will be evaluated by independent assessors, who will be supported by new assessment approaches from C-CAGI. Results will be presented at CAGI experiment conferences with deep technical engagement, which will be interleaved with reflective CAGIâ meetings that create an environment for a comprehensive evaluation of the field, facilitating identification of major bottlenecks and problems faced by the current genome interpretation approaches. 3. Broadly disseminate the results and conclusions from the CAGI experiments and analysis. C-CAGI will outreach to the broader scientific and clinical community through its publications, and the creation of a calibrated reference integrated into the most common workflows for ready adoption. CAGI will also be represented at international meetings with presentations and workshops. 4. Operate effectively and responsively. C-CAGI will operate efficiently as it closely interacts with hundreds of participants. CAGI will build upon a robust information infrastructure that securely facilitates data dissemination, prediction submission, and assessment.
期刊论文(63)
专著(0)
科研奖励(0)
会议论文
Determination of disease phenotypes and pathogenic variants from exome sequence data in the CAGI 4 gene panel challenge.
在CAGI 4基因面板挑战中,从外显子组序列数据中确定疾病表型和致病变异。
DOI: 10.1002/humu.23249
发表时间: 2017-09
期刊: Human mutation
影响因子: 3.9
作者: [Kundu K, Pal LR, Yin Y, Moult J]
通讯作者: Moult J
CAGI6 ID-Challenge: Assessment of phenotype and variant predictions in 415 children with Neurodevelopmental Disorders (NDDs).
CAGI6 ID-Challenge:评估 415 名患有神经发育障碍 (NDD) 的儿童的表型和变异预测。
DOI: 10.21203/rs.3.rs-3209168/v1
发表时间: 2023
期刊: Research square
影响因子: --
作者: [Aspromonte,MariaCristina, Conte,AlessioDel, Zhu,Shaowen, Tan,Wuwei, Shen,Yang, Zhang,Yexian, Li,Qi, Wang,MaggieHaitian, Babbi,Giulia, Bovo,Samuele, Martelli,PierLuigi, Casadio,Rita, Althagafi,Azza, Toonsi,Sumyyah, Kulmanov,Maxat, Hoehnd]
通讯作者: Hoehnd
Precision Medicine: Addressing the Challenges of Sharing, Analysis, and Privacy at Scale.
精准医学:应对大规模共享、分析和隐私的挑战。
DOI: --
发表时间: 2020
期刊: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
影响因子: --
作者: [Brenner,StevenE, Bulyk,MarthaL, Crawford,DanaC, Morgan,AlexanderA, Radivojac,Predrag, Tatonetti,NicholasP]
通讯作者: Tatonetti,NicholasP
DOI: 10.1002/humu.23280
发表时间: 2017-09
期刊: Human mutation
影响因子: 3.9
作者: [Daneshjou R, Wang Y, Bromberg Y, Bovo S, Martelli PL, Babbi G, Lena PD, Casadio R, Edwards M, Gifford D, Jones DT, Sundaram L, Bhat RR, Li X, Pal LR, Kundu K, Yin Y, Moult J, Jiang Y, Pejaver V, Pagel KA, Li B, Mooney SD, Radivojac P, Shah S, Carraro M, Gasparini A, Leonardi E, Giollo M, Ferrari C, Tosatto SCE, Bachar E, Azaria JR, Ofran Y, Unger R, Niroula A, Vihinen M, Chang B, Wang MH, Franke A, Petersen BS, Pirooznia M, Zandi P, McCombie R, Potash JB, Altman RB, Klein TE, Hoskins RA, Repo S, Brenner SE, Morgan AA]
通讯作者: Morgan AA
33
    Identification of Candidate Disease-Causing Variants
    Informatics Infrastructure and Bioinformatics Analysis
    Identification of Candidate Disease-Causing Variants
    Identification of Candidate Disease-Causing Variants
    海外基金