{"id":"https://openalex.org/W4391673325","doi":"https://doi.org/10.48550/arxiv.2402.04845","title":"AlphaFold Meets Flow Matching for Generating Protein Ensembles","display_name":"AlphaFold Meets Flow Matching for Generating Protein Ensembles","publication_year":2024,"publication_date":"2024-02-07","ids":{"openalex":"https://openalex.org/W4391673325","doi":"https://doi.org/10.48550/arxiv.2402.04845"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2402.04845","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2402.04845","pdf_url":"https://arxiv.org/pdf/2402.04845","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2402.04845","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074077264","display_name":"Bowen Jing","orcid":"https://orcid.org/0000-0003-0843-6979"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jing, Bowen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044078921","display_name":"Bonnie Berger","orcid":"https://orcid.org/0000-0002-2724-7228"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berger, Bonnie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5048915657","display_name":"Tommi Jaakkola","orcid":"https://orcid.org/0000-0002-2199-0379"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jaakkola, Tommi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074077264"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":75,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10519","display_name":"Advanced Proteomics Techniques and Applications","score":0.9311000108718872,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10519","display_name":"Advanced Proteomics Techniques and Applications","score":0.9311000108718872,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6535211205482483},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5387232303619385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47081074118614197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32411715388298035},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20042958855628967},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0812230110168457},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07085642218589783}],"concepts":[{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6535211205482483},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5387232303619385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47081074118614197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32411715388298035},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20042958855628967},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0812230110168457},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07085642218589783}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2402.04845","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2402.04845","pdf_url":"https://arxiv.org/pdf/2402.04845","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2402.04845","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2402.04845","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2402.04845","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2402.04845","pdf_url":"https://arxiv.org/pdf/2402.04845","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1046996932","display_name":null,"funder_award_id":"1R35GM141861","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G1065316766","display_name":null,"funder_award_id":"Award","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G2082912093","display_name":null,"funder_award_id":"1918839","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2450996201","display_name":null,"funder_award_id":"DE-SC0022158","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G3476229289","display_name":null,"funder_award_id":"DE-SC0022158","funder_id":"https://openalex.org/F4320332359","funder_display_name":"Office of Science"},{"id":"https://openalex.org/G434798111","display_name":null,"funder_award_id":"27818","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G4369507515","display_name":null,"funder_award_id":"NERSC","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G473593538","display_name":null,"funder_award_id":"Molecular","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G5241959708","display_name":null,"funder_award_id":"DE-SC0022158","funder_id":"https://openalex.org/F4320337506","funder_display_name":"Advanced Scientific Computing Research"},{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6755165505","display_name":null,"funder_award_id":"award","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6894402473","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7908228807","display_name":null,"funder_award_id":"Molecular","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8012526549","display_name":null,"funder_award_id":"R35GM141861","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8355252386","display_name":null,"funder_award_id":"1R35GM141861","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8518419178","display_name":null,"funder_award_id":"R35GM141861","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320317220","display_name":"National Energy Research Scientific Computing Center","ror":"https://ror.org/05v3mvq14"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320332186","display_name":"Defense Threat Reduction Agency","ror":"https://ror.org/04tz64554"},{"id":"https://openalex.org/F4320332359","display_name":"Office of Science","ror":"https://ror.org/00mmn6b08"},{"id":"https://openalex.org/F4320337253","display_name":"Instituto de Ciencias del Mar y Limnolog\u00eda, Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":null},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"},{"id":"https://openalex.org/F4320337506","display_name":"Advanced Scientific Computing Research","ror":"https://ror.org/0012c7r22"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391673325.pdf","grobid_xml":"https://content.openalex.org/works/W4391673325.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655"],"abstract_inverted_index":{"The":[0],"biological":[1],"functions":[2],"of":[3,28,55,75],"proteins":[4],"often":[5],"depend":[6],"on":[7,66,88],"dynamic":[8],"structural":[9],"ensembles.":[10],"In":[11],"this":[12],"work,":[13],"we":[14],"develop":[15],"a":[16,45,72,113,133],"flow-based":[17],"generative":[18,53],"modeling":[19],"approach":[20],"for":[21,105,135],"learning":[22],"and":[23,39,41,60,64,77,101],"sampling":[24],"the":[25,67],"conformational":[26,97],"landscapes":[27],"proteins.":[29,107],"We":[30],"repurpose":[31],"highly":[32],"accurate":[33],"single-state":[34],"predictors":[35],"such":[36],"as":[37,132],"AlphaFold":[38,81],"ESMFold":[40],"fine-tune":[42],"them":[43],"under":[44],"custom":[46],"flow":[47],"matching":[48],"framework":[49],"to":[50,80,121],"obtain":[51],"sequence-conditoned":[52],"models":[54],"protein":[56],"structure":[57,116],"called":[58],"AlphaFlow":[59],"ESMFlow.":[61],"When":[62,85],"trained":[63,87],"evaluated":[65],"PDB,":[68],"our":[69,93,109],"method":[70,94,110],"provides":[71],"superior":[73],"combination":[74],"precision":[76],"diversity":[78],"compared":[79],"with":[82,117],"MSA":[83],"subsampling.":[84],"further":[86],"ensembles":[89],"from":[90],"all-atom":[91],"MD,":[92],"accurately":[95],"captures":[96],"flexibility,":[98],"positional":[99],"distributions,":[100],"higher-order":[102],"ensemble":[103],"observables":[104],"unseen":[106],"Moreover,":[108],"can":[111],"diversify":[112],"static":[114],"PDB":[115],"faster":[118],"wall-clock":[119],"convergence":[120],"certain":[122],"equilibrium":[123],"properties":[124],"than":[125],"replicate":[126],"MD":[127],"trajectories,":[128],"demonstrating":[129],"its":[130],"potential":[131],"proxy":[134],"expensive":[136],"physics-based":[137],"simulations.":[138],"Code":[139],"is":[140],"available":[141],"at":[142],"https://github.com/bjing2016/alphaflow.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":45},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}