{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T09:45:54Z","timestamp":1758361554911,"version":"3.44.0"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T00:00:00Z","timestamp":1754870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>High-throughput sequencing uncovers how B-cells adapt in response to antigens by generating B-cell-receptor (BCR) sequences at an unprecedented scale. As BCR datasets grow to millions of sequences, using efficient computational methods becomes crucial. One important aspect of antibody sequence analysis is detecting clonal families or clusters of related sequences, whether they come from immunization, synthetic-libraries or even ML-generated datasets.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We introduce deepNGS Navigator, a computational tool that leverages language models and contrastive learning to transform antibody sequences into intuitive 2D representations. The resulting 2D maps offer a visualization of overall diversity of input datasets, which can be clustered based on the sequence distances and their densities across the map. Beyond grouping related sequences, the 2D maps also represent mutational patterns inferred from sequence embeddings, enabling trajectory analysis and clustering within the projected space. By overlaying properties such as charge, the map helps identify clusters of interest for further investigation while also flagging potentially noisy or non-specific sequences with higher risk. We demonstrate deepNGS Navigator\u2019s utilities on several datasets, including: (i) a synthetic-library from a yeast-display targeting HER2, (ii) a machine learning-generated dataset with a hierarchical structure, (iii) NGS sequences from a llama immunized against COVID RBD, (iv) human naive and memory B-cell sequences, and (v) an in silico dataset simulating B-cell clonal lineages.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The deepNGS Navigator source code is available at: github.com\/prescient-design\/deepngs-navigator and github.com\/prescient-design\/deepngs-navigator-panel-app.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf414","type":"journal-article","created":{"date-parts":[[2025,8,10]],"date-time":"2025-08-10T11:40:41Z","timestamp":1754826041000},"source":"Crossref","is-referenced-by-count":0,"title":["deepNGS navigator: exploring antibody NGS datasets using deep contrastive learning"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1308-4659","authenticated-orcid":false,"given":"Homa","family":"MohammadiPeyhani","sequence":"first","affiliation":[{"name":"Prescient Design, Genentech"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7419-4707","authenticated-orcid":false,"given":"Edith","family":"Lee","sequence":"additional","affiliation":[{"name":"Prescient Design, Genentech"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4354-7906","authenticated-orcid":false,"given":"Richard","family":"Bonneau","sequence":"additional","affiliation":[{"name":"Prescient Design, Genentech"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5165-0973","authenticated-orcid":false,"given":"Vladimir","family":"Gligorijevic","sequence":"additional","affiliation":[{"name":"Prescient Design, Genentech"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0860-1890","authenticated-orcid":false,"given":"Jae Hyeon","family":"Lee","sequence":"additional","affiliation":[{"name":"Prescient Design, Genentech"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2025,8,11]]},"reference":[{"key":"2025091914030444100_btaf414-B1","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1186\/s12859-022-05112-z","article-title":"Reconstructing b cell lineage trees with minimum spanning tree and genotype abundances","volume":"24","author":"Abdollahi","year":"2023","journal-title":"BMC Bioinformatics"},{"key":"2025091914030444100_btaf414-B2","doi-asserted-by":"publisher","first-page":"e1010411","DOI":"10.1371\/journal.pcbi.1010411","article-title":"A multi-objective based clustering for inferring bcr clonal lineages from high-throughput B cell repertoire data","volume":"18","author":"Abdollahi","year":"2022","journal-title":"PLoS Comput Biol"},{"key":"2025091914030444100_btaf414-B3","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1145\/361002.361007","article-title":"Multidimensional binary search trees used for associative searching","volume":"18","author":"Bentley","year":"1975","journal-title":"Commun ACM"},{"year":"2022","author":"B\u00f6hm","key":"2025091914030444100_btaf414-B4"},{"year":"2020","author":"Chen","key":"2025091914030444100_btaf414-B5"},{"key":"2025091914030444100_btaf414-B6","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkaf025","article-title":"Simulation of adaptive immune receptors and repertoires with complex immune information to guide the development and benchmarking of AIRR machine learning","volume":"53","author":"Chernigovskaya","year":"2025","journal-title":"Nucleic Acids Res."},{"year":"2018","author":"Devlin","key":"2025091914030444100_btaf414-B7"},{"key":"2025091914030444100_btaf414-B8","doi-asserted-by":"publisher","first-page":"960","DOI":"10.1038\/s41587-024-02346-5","article-title":"Rapid discovery of monoclonal antibodies by microfluidics-enabled facs of single pathogen-specific antibody-secreting cells","volume":"43","author":"Fischer","year":"2025","journal-title":"Nat Biotechnol"},{"key":"2025091914030444100_btaf414-B9","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1186\/s12929-024-01018-5","article-title":"The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design","volume":"31","author":"Gallo","year":"2024","journal-title":"J Biomed Sci"},{"year":"2024","author":"Ghraichy","key":"2025091914030444100_btaf414-B10"},{"key":"2025091914030444100_btaf414-B11","doi-asserted-by":"publisher","first-page":"eabm0220","DOI":"10.1126\/sciadv.abm0220","article-title":"Multivariate mining of an alpaca immune repertoire identifies potent cross-neutralizing sars-cov-2 nanobodies","volume":"8","author":"Hanke","year":"2022","journal-title":"Sci Adv"},{"key":"2025091914030444100_btaf414-B12","doi-asserted-by":"publisher","first-page":"20140239","DOI":"10.1098\/rstb.2014.0239","article-title":"The analysis of clonal expansions in normal and autoimmune B cell repertoires","volume":"370","author":"Hershberg","year":"2015","journal-title":"Philos Trans R Soc Lond B Biol Sci"},{"key":"2025091914030444100_btaf414-B13","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1006\/jmbi.2001.4662","article-title":"Yet another numbering scheme for immunoglobulin variable domains: an automatic modeling and analysis tool","volume":"309","author":"Honegger","year":"2001","journal-title":"J Mol Biol"},{"key":"2025091914030444100_btaf414-B14","doi-asserted-by":"publisher","first-page":"8382","DOI":"10.1038\/s41467-024-52442-y","article-title":"Rapid affinity optimization of an anti-trem2 clinical lead antibody by cross-lineage immune repertoire mining","volume":"15","author":"Hsiao","year":"2024","journal-title":"Nat Commun"},{"key":"2025091914030444100_btaf414-B15","doi-asserted-by":"publisher","first-page":"185","DOI":"10.3390\/bioengineering11020185","article-title":"Leveraging artificial intelligence to expedite antibody design and enhance antibody\u2013antigen interactions","volume":"11","author":"Kim","year":"2024","journal-title":"Bioengineering"},{"key":"2025091914030444100_btaf414-B16","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.tips.2022.12.005","article-title":"Computational and artificial intelligence-based methods for antibody development","volume":"44","author":"Kim","year":"2023","journal-title":"Trends Pharmacol Sci"},{"key":"2025091914030444100_btaf414-B17","doi-asserted-by":"publisher","first-page":"e101322","DOI":"10.1371\/journal.pone.0101322","article-title":"Systematic characterization and comparative analysis of the rabbit immunoglobulin repertoire","volume":"9","author":"Lavinder","year":"2014","journal-title":"PLoS One"},{"key":"2025091914030444100_btaf414-B18","doi-asserted-by":"publisher","first-page":"e129","DOI":"10.1093\/nar\/gkab829","article-title":"Bioseq-blm: a platform for analyzing DNA, RNA and protein sequences based on biological language models","volume":"49","author":"Li","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2025091914030444100_btaf414-B19","doi-asserted-by":"publisher","first-page":"3454","DOI":"10.1038\/s41467-023-39022-2","article-title":"Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries","volume":"14","author":"Li","year":"2023","journal-title":"Nat Commun"},{"key":"2025091914030444100_btaf414-B20","doi-asserted-by":"publisher","first-page":"e21","DOI":"10.1093\/nar\/gkaa1160","article-title":"Alignment free identification of clones in b cell receptor repertoires","volume":"49","author":"Lindenbaum","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2025091914030444100_btaf414-B21","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1038\/s42003-022-04129-7","article-title":"Honing-in antigen-specific cells during antibody discovery: a user-friendly process to mine a deeper repertoire","volume":"5","author":"Mahendra","year":"2022","journal-title":"Commun Biol"},{"key":"2025091914030444100_btaf414-B22","doi-asserted-by":"publisher","first-page":"W264","DOI":"10.1093\/nar\/gky276","article-title":"Brepertoire: a user-friendly web server for analysing antibody repertoire data","volume":"46","author":"Margreitter","year":"2018","journal-title":"Nucleic Acids Res"},{"year":"2020","author":"McInnes","key":"2025091914030444100_btaf414-B23"},{"key":"2025091914030444100_btaf414-B24","doi-asserted-by":"publisher","DOI":"10.1016\/j.cels.2023.12.003","article-title":"Meta learning addresses noisy and under-labeled data in machine learning-guided antibody engineering","volume":"15","author":"Minot","year":"2024","journal-title":"Cell Syst"},{"key":"2025091914030444100_btaf414-B25","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1016\/j.it.2022.01.003","article-title":"Unraveling b cell trajectories at single cell resolution","volume":"43","author":"Morgan","year":"2022","journal-title":"Trends Immunol"},{"key":"2025091914030444100_btaf414-B26","doi-asserted-by":"publisher","first-page":"1549","DOI":"10.1093\/bib\/bbz095","article-title":"Computational approaches to therapeutic antibody design: established methods and emerging trends","volume":"21","author":"Norman","year":"2020","journal-title":"Brief Bioinform"},{"key":"2025091914030444100_btaf414-B27","doi-asserted-by":"publisher","first-page":"i341","DOI":"10.1093\/bioinformatics\/bty235","article-title":"A spectral clustering-based method for identifying clones from high-throughput b cell repertoire sequencing data","volume":"34","author":"Nouri","year":"2018","journal-title":"Bioinformatics"},{"key":"2025091914030444100_btaf414-B28","doi-asserted-by":"publisher","first-page":"vbac046","DOI":"10.1093\/bioadv\/vbac046","article-title":"Ablang: an antibody language model for completing antibody sequences","volume":"2","author":"Olsen","year":"2022","journal-title":"Bioinform Adv"},{"key":"2025091914030444100_btaf414-B29","doi-asserted-by":"publisher","first-page":"e1005086","DOI":"10.1371\/journal.pcbi.1005086","article-title":"Likelihood-based inference of b cell clonal families","volume":"12","author":"Ralph","year":"2016","journal-title":"PLoS Comput Biol"},{"key":"2025091914030444100_btaf414-B30","doi-asserted-by":"publisher","DOI":"10.3389\/fddsv.2024.1447867","article-title":"Ai-accelerated therapeutic antibody development: practical insights","volume":"4","author":"Santuari","year":"2024","journal-title":"Front Drug Discov"},{"key":"2025091914030444100_btaf414-B31","doi-asserted-by":"publisher","first-page":"2115200","DOI":"10.1080\/19420862.2022.2115200","article-title":"Simultaneous affinity maturation and developability enhancement using natural liability-free cdrs","volume":"14","author":"Teixeira","year":"2022","journal-title":"mAbs"},{"key":"2025091914030444100_btaf414-B32","doi-asserted-by":"publisher","first-page":"5233","DOI":"10.1038\/s41598-019-41695-z","article-title":"From louvain to leiden: guaranteeing well-connected communities","volume":"9","author":"Traag","year":"2019","journal-title":"Sci Rep"},{"key":"2025091914030444100_btaf414-B33","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der Maaten","journal-title":"J Mach Learn Res"},{"key":"2025091914030444100_btaf414-B34","doi-asserted-by":"publisher","first-page":"100601","DOI":"10.1016\/j.crmeth.2023.100601","article-title":"Fast clonal family inference from large-scale B cell repertoire sequencing data","volume":"3","author":"Wang","year":"2023","journal-title":"Cell Rep Methods"},{"key":"2025091914030444100_btaf414-B35","doi-asserted-by":"publisher","first-page":"104025","DOI":"10.1016\/j.drudis.2024.104025","article-title":"Best practices for machine learning in antibody discovery and development","volume":"29","author":"Wossnig","year":"2024","journal-title":"Drug Discovery Today"},{"key":"2025091914030444100_btaf414-B36","doi-asserted-by":"publisher","first-page":"3938","DOI":"10.1093\/bioinformatics\/btx533","article-title":"Comparison of methods for phylogenetic b-cell lineage inference using time-resolved antibody repertoire simulations (ABSIM)","volume":"33","author":"Yermanos","year":"2017","journal-title":"Bioinformatics"},{"key":"2025091914030444100_btaf414-B37","doi-asserted-by":"publisher","first-page":"2149","DOI":"10.3389\/fimmu.2018.02149","article-title":"Tracing antibody repertoire evolution by systems phylogeny","volume":"9","author":"Yermanos","year":"2018","journal-title":"Front Immunol"},{"year":"2024","author":"Zheng","key":"2025091914030444100_btaf414-B38"},{"key":"2025091914030444100_btaf414-B39","doi-asserted-by":"publisher","first-page":"W17","DOI":"10.1093\/nar\/gkad400","article-title":"Abalign: a comprehensive multiple sequence alignment platform for b-cell receptor immune repertoires","volume":"51","author":"Zong","year":"2023","journal-title":"Nucleic Acids Res"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaf414\/64014881\/btaf414.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/41\/9\/btaf414\/64014881\/btaf414.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/41\/9\/btaf414\/64014881\/btaf414.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T18:03:17Z","timestamp":1758304997000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btaf414\/8231071"}},"subtitle":[],"editor":[{"given":"Can","family":"Alkan","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2025,8,11]]},"references-count":39,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,9,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaf414","relation":{},"ISSN":["1367-4811"],"issn-type":[{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2025,9]]},"published":{"date-parts":[[2025,8,11]]},"article-number":"btaf414"}}