{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T21:33:59Z","timestamp":1784583239750,"version":"3.55.0"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T00:00:00Z","timestamp":1681948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972100"],"award-info":[{"award-number":["61972100"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172300"],"award-info":[{"award-number":["62172300"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Predicting molecular properties is one of the fundamental problems in drug design and discovery. In recent years, self-supervised learning (SSL) has shown its promising performance in image recognition, natural language processing, and single-cell data analysis. Contrastive learning (CL) is a typical SSL method used to learn the features of data so that the trained model can more effectively distinguish the data. One important issue of CL is how to select positive samples for each training example, which will significantly impact the performance of CL.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this article, we propose a new method for molecular property prediction (MPP) by Contrastive\u2002Learning with\u2002Attention-guided\u2002Positive-sample\u2002Selection (CLAPS). First, we generate positive samples for each training example based on an attention-guided selection scheme. Second, we employ a Transformer encoder to extract latent feature vectors and compute the contrastive loss aiming to distinguish positive and negative sample pairs. Finally, we use the trained encoder for predicting molecular properties. Experiments on various benchmark datasets show that our approach outperforms the state-of-the-art (SOTA) methods in most cases.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The code is publicly available at https:\/\/github.com\/wangjx22\/CLAPS.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad258","type":"journal-article","created":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T18:29:41Z","timestamp":1682015381000},"source":"Crossref","is-referenced-by-count":23,"title":["Molecular property prediction by contrastive learning with attention-guided positive sample selection"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0432-2811","authenticated-orcid":false,"given":"Jinxian","family":"Wang","sequence":"first","affiliation":[{"name":"Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science , Fudan University, 2005 Songhu Road , Shanghai 200438, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jihong","family":"Guan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai 201804, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1949-2768","authenticated-orcid":false,"given":"Shuigeng","family":"Zhou","sequence":"additional","affiliation":[{"name":"Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science , Fudan University, 2005 Songhu Road , Shanghai 200438, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,4,20]]},"reference":[{"key":"2023051701233320100_btad258-B1","first-page":"524","author":"Batson","year":"2019"},{"key":"2023051701233320100_btad258-B2","doi-asserted-by":"crossref","first-page":"2887","DOI":"10.1021\/jm9602928","article-title":"The properties of known drugs. 1. 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