Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing最新文献_第10页

Session Introduction: Graph Representations and Algorithms in Biomedicine. 会议介绍:生物医学中的图形表示和算法。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Brianna Chrisman, Maya Varma, Sepideh Maleki, Maria Brbic, Cliff Joslyn, Marinka Zitnik

引用次数: 0

Prediction of Kinase-Substrate Associations Using The Functional Landscape of Kinases and Phosphorylation Sites. 利用激酶和磷酸化位点的功能图谱预测激酶与底物的联系

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Marzieh Ayati, Serhan Yilmaz, Filipa Blasco Tavares Pereira Lopes, Mark Chance, Mehmet Koyuturk

{"title":"Prediction of Kinase-Substrate Associations Using The Functional Landscape of Kinases and Phosphorylation Sites.","authors":"Marzieh Ayati, Serhan Yilmaz, Filipa Blasco Tavares Pereira Lopes, Mark Chance, Mehmet Koyuturk","doi":"","DOIUrl":"","url":null,"abstract":"Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships and associations among phosphosites and kinases. To construct a phosphosite-phosphosite association network, we use sequence similarity, shared biological pathways, co-evolution, co-occurrence, and co-phosphorylation of phosphosites across different biological states. To construct a kinase-kinase association network, we integrate protein-protein interactions, shared biological pathways, and membership in common kinase families. We use node embeddings computed from these heterogeneous networks to train machine learning models for predicting kinase-substrate associations. Our systematic computational experiments using the PhosphositePLUS database shows that the resulting algorithm, NetKSA, outperforms two state-of-the-art algorithms, including KinomeXplorer and LinkPhinder, in overall KSA prediction. By stratifying the ranking of kinases, NetKSA also enables annotation of phosphosites that are targeted by relatively less-studied kinases.Availability: The code and data are available at compbio.case.edu/NetKSA/.","PeriodicalId":34954,"journal":{"name":"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing","volume":"28 ","pages":"73-84"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b4/25/nihms-1852984.PMC9782723.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10276758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FairPRS: adjusting for admixed populations in polygenic risk scores using invariant risk minimization. FairPRS：使用不变量风险最小化方法调整多基因风险评分中的混杂人群。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Diego Machado Reyes, Aritra Bose, Ehud Karavani, Laxmi Parida

引用次数: 0

Development and application of a computable genotype model in the GA4GH Variation Representation Specification. 在 GA4GH 变异表示规范中开发和应用可计算基因型模型。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Wesley Goar, Lawrence Babb, Srikar Chamala, Melissa Cline, Robert R Freimuth, Reece K Hart, Kori Kuzma, Jennifer Lee, Tristan Nelson, Andreas Prlić, Kevin Riehle, Anastasia Smith, Kathryn Stahl, Andrew D Yates, Heidi L Rehm, Alex H Wagner

{"title":"Development and application of a computable genotype model in the GA4GH Variation Representation Specification.","authors":"Wesley Goar, Lawrence Babb, Srikar Chamala, Melissa Cline, Robert R Freimuth, Reece K Hart, Kori Kuzma, Jennifer Lee, Tristan Nelson, Andreas Prlić, Kevin Riehle, Anastasia Smith, Kathryn Stahl, Andrew D Yates, Heidi L Rehm, Alex H Wagner","doi":"","DOIUrl":"","url":null,"abstract":"As the diversity of genomic variation data increases with our growing understanding of the role of variation in health and disease, it is critical to develop standards for precise inter-system exchange of these data for research and clinical applications. The Global Alliance for Genomics and Health (GA4GH) Variation Representation Specification (VRS) meets this need through a technical terminology and information model for disambiguating and concisely representing variation concepts. Here we discuss the recent Genotype model in VRS, which may be used to represent the allelic composition of a genetic locus. We demonstrate the use of the Genotype model and the constituent Haplotype model for the precise and interoperable representation of pharmacogenomic diplotypes, HGVS variants, and VCF records using VRS and discuss how this can be leveraged to enable interoperable exchange and search operations between assayed variation and genomic knowledgebases.","PeriodicalId":34954,"journal":{"name":"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing","volume":"28 ","pages":"383-394"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d8/6e/nihms-1853002.PMC9782714.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9698793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accessing clinical-grade genomic classification data through the ClinGen Data Platform. 通过ClinGen数据平台访问临床级基因组分类数据。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Karen P Dalton, Heidi L Rehm, Matt W Wright, Mark E Mandell, Kilannin Krysiak, Lawrence Babb, Kevin Riehle, Tristan Nelson, Alex H Wagner

引用次数: 0

Predictive modeling using shape statistics for interpretable and robust quality assurance of automated contours in radiation treatment planning. 利用形状统计进行预测建模，用于放射治疗计划中自动轮廓的可解释性和鲁棒性质量保证。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Zachary T Wooten, Cenji Yu, Laurence E Court, Christine B Peterson

{"title":"Predictive modeling using shape statistics for interpretable and robust quality assurance of automated contours in radiation treatment planning.","authors":"Zachary T Wooten, Cenji Yu, Laurence E Court, Christine B Peterson","doi":"","DOIUrl":"","url":null,"abstract":"Deep learning methods for image segmentation and contouring are gaining prominence as an automated approach for delineating anatomical structures in medical images during radiation treatment planning. These contours are used to guide radiotherapy treatment planning, so it is important that contouring errors are flagged before they are used for planning. This creates a need for effective quality assurance methods to enable the clinical use of automated contours in radiotherapy. We propose a novel method for contour quality assurance that requires only shape features, making it independent of the platform used to obtain the images. Our method uses a random forest classifier to identify low-quality contours. On a dataset of 312 kidney contours, our method achieved a cross-validated area under the curve of 0.937 in identifying unacceptable contours. We applied our method to an unlabeled validation dataset of 36 kidney contours. We flagged 6 contours which were then reviewed by a cervix contour specialist, who found that 4 of the 6 contours contained errors. We used Shapley values to characterize the specific shape features that contributed to each contour being flagged, providing a starting point for characterizing the source of the contouring error. These promising results suggest our method is feasible for quality assurance of automated radiotherapy contours.","PeriodicalId":34954,"journal":{"name":"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing","volume":"28 ","pages":"395-406"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/97/ce/nihms-1888738.PMC10091357.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9287536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TRANS-OMIC KNOWLEDGE TRANSFER MODELING INFERS GUT MICROBIOME BIOMARKERS OF ANTI-TNF RESISTANCE IN ULCERATIVE COLITIS. 反组知识转移模型推断溃疡性结肠炎中抗肿瘤坏死因子耐药的肠道微生物组生物标志物。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Alan Trinh, Ran Ran, Douglas K Brubaker

{"title":"TRANS-OMIC KNOWLEDGE TRANSFER MODELING INFERS GUT MICROBIOME BIOMARKERS OF ANTI-TNF RESISTANCE IN ULCERATIVE COLITIS.","authors":"Alan Trinh, Ran Ran, Douglas K Brubaker","doi":"","DOIUrl":"","url":null,"abstract":"A critical challenge in analyzing multi-omics data from clinical cohorts is the re-use of these valuable datasets to answer biological questions beyond the scope of the original study. Transfer Learning and Knowledge Transfer approaches are machine learning methods that leverage knowledge gained in one domain to solve a problem in another. Here, we address the challenge of developing Knowledge Transfer approaches to map trans-omic information from a multi-omic clinical cohort to another cohort in which a novel phenotype is measured. Our test case is that of predicting gut microbiome and gut metabolite biomarkers of resistance to anti-TNF therapy in Ulcerative Colitis patients. Three approaches are proposed for Trans-omic Knowledge Transfer, and the resulting performance and downstream inferred biomarkers are compared to identify efficacious methods. We find that multiple approaches reveal similar metabolite and microbial biomarkers of anti-TNF resistance and that these commonly implicated biomarkers can be validated in literature analysis. Overall, we demonstrate a promising approach to maximize the value of the investment in large clinical multi-omics studies by re-using these data to answer biological and clinical questions not posed in the original study.","PeriodicalId":34954,"journal":{"name":"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing","volume":"28 ","pages":"287-298"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10443515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-treatment Effect Estimation from Biomedical Data. 基于生物医学数据的多处理效果估计。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Raquel Aoki, Yizhou Chen, Martin Ester

引用次数: 0

Session Introduction: Precision Medicine: Using Artificial Intelligence to Improve Diagnostics and Healthcare. 会议介绍:精准医疗:利用人工智能改善诊断和医疗保健。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Michelle Whirl-Carrillo, Steven E Brenner, Jonathan H Chen, Dana C Crawford, Łukasz Kidziński, David Ouyang, Roxana Daneshjou

引用次数: 0

HIGH-PERFORMANCE COMPUTING MEETS HIGH-PERFORMANCE MEDICINE. 高性能计算遇上高性能医学。

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Pub Date : 2023-01-01

Anurag Verma, Jennifer Huffman, Ali Torkamani, Ravi Madduri

引用次数: 0