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Annual Review of Biomedical Data Science最新文献

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Machine Learning in Chemoinformatics and Medicinal Chemistry. 化学信息学和药物化学中的机器学习。
IF 6
Annual Review of Biomedical Data Science Pub Date : 2022-04-19 DOI: 10.1146/annurev-biodatasci-122120-124216
Raquel Rodríguez-Pérez, Filip Miljković, J. Bajorath
{"title":"Machine Learning in Chemoinformatics and Medicinal Chemistry.","authors":"Raquel Rodríguez-Pérez, Filip Miljković, J. Bajorath","doi":"10.1146/annurev-biodatasci-122120-124216","DOIUrl":"https://doi.org/10.1146/annurev-biodatasci-122120-124216","url":null,"abstract":"In chemoinformatics and medicinal chemistry, machine learning has evolved into an important approach. In recent years, increasing computational resources and new deep learning algorithms have put machine learning onto a new level, addressing previously unmet challenges in pharmaceutical research. In silico approaches for compound activity predictions, de novo design, and reaction modeling have been further advanced by new algorithmic developments and the emergence of big data in the field. Herein, novel applications of machine learning and deep learning in chemoinformatics and medicinal chemistry are reviewed. Opportunities and challenges for new methods and applications are discussed, placing emphasis on proper baseline comparisons, robust validation methodologies, and new applicability domains. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48421704","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: 6
Static and Motion Facial Analysis for Craniofacial Assessment and Diagnosing Diseases. 静态和运动面部分析用于颅面评估和疾病诊断。
IF 6
Annual Review of Biomedical Data Science Pub Date : 2022-04-19 DOI: 10.1146/annurev-biodatasci-122120-111413
H. Matthews, G. de Jong, T. Maal, P. Claes
{"title":"Static and Motion Facial Analysis for Craniofacial Assessment and Diagnosing Diseases.","authors":"H. Matthews, G. de Jong, T. Maal, P. Claes","doi":"10.1146/annurev-biodatasci-122120-111413","DOIUrl":"https://doi.org/10.1146/annurev-biodatasci-122120-111413","url":null,"abstract":"Deviation from a normal facial shape and symmetry can arise from numerous sources, including physical injury and congenital birth defects. Such abnormalities can have important aesthetic and functional consequences. Furthermore, in clinical genetics distinctive facial appearances are often associated with clinical or genetic diagnoses; the recognition of a characteristic facial appearance can substantially narrow the search space of potential diagnoses for the clinician. Unusual patterns of facial movement and expression can indicate disturbances to normal mechanical functioning or emotional affect. Computational analyses of static and moving 2D and 3D images can serve clinicians and researchers by detecting and describing facial structural, mechanical, and affective abnormalities objectively. In this review we survey traditional and emerging methods of facial analysis, including statistical shape modeling, syndrome classification, modeling clinical face phenotype spaces, and analysis of facial motion and affect. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"1 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41479900","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: 3
The Cell Physiome: What Do We Need in a Computational Physiology Framework for Predicting Single-Cell Biology? 细胞重组:我们在预测单细胞生物学的计算生理学框架中需要什么?
IF 6
Annual Review of Biomedical Data Science Pub Date : 2022-02-27 DOI: 10.1146/annurev-biodatasci-072018-021246
V. Rajagopal, S. Arumugam, Peter J. Hunter, A. Khadangi, Joshua Chung, Michael Pan
{"title":"The Cell Physiome: What Do We Need in a Computational Physiology Framework for Predicting Single-Cell Biology?","authors":"V. Rajagopal, S. Arumugam, Peter J. Hunter, A. Khadangi, Joshua Chung, Michael Pan","doi":"10.1146/annurev-biodatasci-072018-021246","DOIUrl":"https://doi.org/10.1146/annurev-biodatasci-072018-021246","url":null,"abstract":"Modern biology and biomedicine are undergoing a big data explosion, needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome project: a framework and approach for creating, sharing, and using biophysics-based computational models of single-cell physiology. Using examples in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date toward creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and reusability of computational models of cells at scale. We conclude with a look forward at steps that will help fully realize this exciting new field of mechanistic biomedical data science. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44647308","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: 5
Best Practices on Big Data Analytics to Address Sex-Specific Biases in our Understanding of the Etiology, Diagnosis and Prognosis of Diseases 大数据分析的最佳实践，以解决我们对疾病病因、诊断和预后的理解中的性别特异性偏差
IF 6
Annual Review of Biomedical Data Science Pub Date : 2022-02-06 DOI: 10.1101/2022.01.31.22270183
S. Golder, K. O’Connor, Yunwen Wang, R. Stevens, G. Gonzalez-Hernandez
{"title":"Best Practices on Big Data Analytics to Address Sex-Specific Biases in our Understanding of the Etiology, Diagnosis and Prognosis of Diseases","authors":"S. Golder, K. O’Connor, Yunwen Wang, R. Stevens, G. Gonzalez-Hernandez","doi":"10.1101/2022.01.31.22270183","DOIUrl":"https://doi.org/10.1101/2022.01.31.22270183","url":null,"abstract":"A bias in health research to favor understanding of diseases as they present in men can have a grave impact on the health of women. This paper reports on a conceptual review of the literature that used machine learning or NLP techniques to interrogate big data for identifying sex-specific health disparities. We searched Ovid MEDLINE, Embase, and PsycINFO in October 2021 using synonyms and indexing terms for (1) \"women\" or \"men\" or \"sex,\" (2) \"big data\" or \"artificial intelligence\" or \"NLP\", and (3) \"disparities\" or \"differences.\" From 902 records, 22 studies met the inclusion criteria and were analyzed. Results demonstrate that the inclusion by sex is inconsistent and often unreported, although the inclusion of men in the included studies is disproportionately less than women. Even though AI and NLP techniques are widely applied in health research, few studies use them to take advatage of unstructured text to investigate sex-related differences or disparities. Researchers are increasingly aware of sex-based data bias, but the process to- wards correction is slow. We reflected on what would be the best practices on using big data analytics to address sex-specific biases in understanding the etiology, diagnosis, and prognosis of diseases.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2022-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44284431","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: 1
Neoantigen Controversies. 新抗原争议。
IF 7
Annual Review of Biomedical Data Science Pub Date : 2021-07-20 Epub Date: 2021-05-11 DOI: 10.1146/annurev-biodatasci-092820-112713
Andrea Castro, Maurizio Zanetti, Hannah Carter
{"title":"Neoantigen Controversies.","authors":"Andrea Castro, Maurizio Zanetti, Hannah Carter","doi":"10.1146/annurev-biodatasci-092820-112713","DOIUrl":"10.1146/annurev-biodatasci-092820-112713","url":null,"abstract":"<p><p>Next-generation sequencing technologies have revolutionized our ability to catalog the landscape of somatic mutations in tumor genomes. These mutations can sometimes create so-called neoantigens, which allow the immune system to detect and eliminate tumor cells. However, efforts that stimulate the immune system to eliminate tumors based on their molecular differences have had less success than has been hoped for, and there are conflicting reports about the role of neoantigens in the success of this approach. Here we review some of the conflicting evidence in the literature and highlight key aspects of the tumor-immune interface that are emerging as major determinants of whether mutation-derived neoantigens will contribute to an immunotherapy response. Accounting for these factors is expected to improve success rates of future immunotherapy approaches.</p>","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"4 ","pages":"227-253"},"PeriodicalIF":7.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10146390/pdf/nihms-1877401.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9746249","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
Research progress of incremental hemodialysis 增量式血液透析的研究进展
IF 6
Annual Review of Biomedical Data Science Pub Date : 2021-01-01 DOI: 10.47297/wspbdswsp2752-630505.20210102
Weiwei Hu, Wenjun Zhang, Y. Qi, Jianqin Wang
{"title":"Research progress of incremental hemodialysis","authors":"Weiwei Hu, Wenjun Zhang, Y. Qi, Jianqin Wang","doi":"10.47297/wspbdswsp2752-630505.20210102","DOIUrl":"https://doi.org/10.47297/wspbdswsp2752-630505.20210102","url":null,"abstract":"","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"5 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86928305","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
A Semantic Ontology Structure－based Approach for Re⁃trieving Similar Medical Images 基于语义本体结构的相似医学图像检索方法
IF 6
Annual Review of Biomedical Data Science Pub Date : 2021-01-01 DOI: 10.47297/wspbdswsp2752-630501.20210102
Yiwen Wang
{"title":"A Semantic Ontology Structure－based Approach for Re⁃\u0000trieving Similar Medical Images","authors":"Yiwen Wang","doi":"10.47297/wspbdswsp2752-630501.20210102","DOIUrl":"https://doi.org/10.47297/wspbdswsp2752-630501.20210102","url":null,"abstract":"","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"1 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78541590","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
Alpha to beta cell reprogramming to treat Type 1 diabetes 细胞重编程治疗1型糖尿病
IF 6
Annual Review of Biomedical Data Science Pub Date : 2021-01-01 DOI: 10.47297/wspbdswsp2752-630504.20210102
V. Li
{"title":"Alpha to beta cell reprogramming to treat Type 1 diabetes","authors":"V. Li","doi":"10.47297/wspbdswsp2752-630504.20210102","DOIUrl":"https://doi.org/10.47297/wspbdswsp2752-630504.20210102","url":null,"abstract":"","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"9 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77628998","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
Establishment of Visual Fear Conditioning in Long－evansRats 长时间迁徙大鼠视觉恐惧条件反射的建立
IF 6
Annual Review of Biomedical Data Science Pub Date : 2021-01-01 DOI: 10.47297/wspbdswsp2752-630502.20210102
Xiaoyuan Li, Yun Liu, Hongyu Si, Peng Wu, Zhenlong Wang
{"title":"Establishment of Visual Fear Conditioning in Long－evans\u0000Rats","authors":"Xiaoyuan Li, Yun Liu, Hongyu Si, Peng Wu, Zhenlong Wang","doi":"10.47297/wspbdswsp2752-630502.20210102","DOIUrl":"https://doi.org/10.47297/wspbdswsp2752-630502.20210102","url":null,"abstract":"","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"16 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78299773","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
Genomic Characteristics of SARS-CoV, MERS-CoV and2019-nCoV SARS-CoV、MERS-CoV和2019- ncov的基因组特征
IF 6
Annual Review of Biomedical Data Science Pub Date : 2021-01-01 DOI: 10.47297/wspbdswsp2752-630503.20210102
Tong Li, Xing Yu, Mengxiang Chen, Y. Lv, W. Zha
{"title":"Genomic Characteristics of SARS-CoV, MERS-CoV and\u00002019-nCoV","authors":"Tong Li, Xing Yu, Mengxiang Chen, Y. Lv, W. Zha","doi":"10.47297/wspbdswsp2752-630503.20210102","DOIUrl":"https://doi.org/10.47297/wspbdswsp2752-630503.20210102","url":null,"abstract":"","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"64 1","pages":""},"PeriodicalIF":6.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76169404","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
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