{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:10Z","timestamp":1772138050419,"version":"3.50.1"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2022,2,10]],"date-time":"2022-02-10T00:00:00Z","timestamp":1644451200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["GM138210"],"award-info":[{"award-number":["GM138210"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Laboratory Directed Research and Development (LDRD) Program of Sandia National Laboratories","award":["2093481"],"award-info":[{"award-number":["2093481"]}]},{"name":"Laboratory Directed Research and Development (LDRD) Program of Sandia National Laboratories","award":["SAND2021-10406"],"award-info":[{"award-number":["SAND2021-10406"]}]},{"name":"Sandia National Laboratories is a multi-mission laboratory managed and operated by the National Technology & Engineering Solutions of Sandia"},{"DOI":"10.13039\/100019966","name":"Honeywell International Inc.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100019966","id-type":"DOI","asserted-by":"crossref"}]},{"name":"U.S. Department of Energy\u2019s National Nuclear Security Administration","award":["DE-NA0003525"],"award-info":[{"award-number":["DE-NA0003525"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,4,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>The goal of oligonucleotide (oligo) design is to select oligos that optimize a set of design criteria. Oligo design problems are combinatorial in nature and require computationally intensive models to evaluate design criteria. Even relatively small problems can be intractable for brute-force approaches that test every possible combination of oligos, so heuristic approaches must be used to find near-optimal solutions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We present a general reinforcement learning (RL) framework, called OligoRL, to solve oligo design problems with complex constraints. OligoRL allows \u2018black-box\u2019 design criteria and can be adapted to solve many oligo design problems. We highlight the flexibility of OligoRL by building tools to solve three distinct design problems: (i) finding pools of random DNA barcodes that lack restriction enzyme recognition sequences (CutFreeRL); (ii) compressing large, non-degenerate oligo pools into smaller degenerate ones (OligoCompressor) and (iii) finding Not-So-Random hexamer primer pools that avoid rRNA and other unwanted transcripts during RNA-seq library preparation (NSR-RL). OligoRL demonstrates how RL offers a general solution for complex oligo design problems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>OligoRL and all simulation codes are available as a Julia package at http:\/\/jensenlab.net\/tools and archived at https:\/\/archive.softwareheritage.org\/browse\/origin\/directory\/?origin_url=https:\/\/github.com\/bmdavid2\/OligoRL.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac073","type":"journal-article","created":{"date-parts":[[2022,2,2]],"date-time":"2022-02-02T15:23:48Z","timestamp":1643815428000},"page":"2219-2225","source":"Crossref","is-referenced-by-count":2,"title":["A reinforcement learning framework for pooled oligonucleotide design"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1995-5766","authenticated-orcid":false,"given":"Benjamin M","family":"David","sequence":"first","affiliation":[{"name":"Department of Bioengineering, University of Illinois at Urbana-Champaign , Urbana, IL 61801, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9959-2197","authenticated-orcid":false,"given":"Ryan M","family":"Wyllie","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of Illinois at Urbana-Champaign , Urbana, IL 61801, USA"}]},{"given":"Ramdane","family":"Harouaka","sequence":"additional","affiliation":[{"name":"Biotechnology and Bioengineering Department, Sandia National Laboratories , Livermore, CA 94550, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1257-9836","authenticated-orcid":false,"given":"Paul A","family":"Jensen","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of Illinois at Urbana-Champaign , Urbana, IL 61801, USA"},{"name":"Department of Microbiology, University of Illinois at Urbana-Champaign , Urbana, IL 61801, USA"},{"name":"Carl R. 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