{"id":"https://openalex.org/W7163035319","doi":"https://doi.org/10.48550/arxiv.2605.31522","title":"Chem-PerturBridge: a harmonized compendium of small molecule perturbation transcriptomic effects","display_name":"Chem-PerturBridge: a harmonized compendium of small molecule perturbation transcriptomic effects","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163035319","doi":"https://doi.org/10.48550/arxiv.2605.31522"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.31522","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31522","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.31522","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060683671","display_name":"Artur Sza\u0142ata","orcid":"https://orcid.org/0000-0001-8413-234X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sza\u0142ata, Artur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089466739","display_name":"Olga Novitskaia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Novitskaia, Olga","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033126809","display_name":"Maiia Shulman","orcid":"https://orcid.org/0009-0006-6308-1997"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shulman, Maiia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137565726","display_name":"Matthew Mella","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mella, Matthew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048789631","display_name":"Altynbek Zhubanchaliyev","orcid":"https://orcid.org/0000-0001-7469-4613"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhubanchaliyev, Altynbek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137513811","display_name":"Fabian J. Theis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Theis, Fabian J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.3100999891757965,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.3100999891757965,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.21299999952316284,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.17790000140666962,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/replicate","display_name":"Replicate","score":0.663100004196167},{"id":"https://openalex.org/keywords/transcriptome","display_name":"Transcriptome","score":0.6313999891281128},{"id":"https://openalex.org/keywords/compendium","display_name":"Compendium","score":0.5773000121116638},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5394999980926514},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5030999779701233},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.48559999465942383},{"id":"https://openalex.org/keywords/small-molecule","display_name":"Small molecule","score":0.4399000108242035}],"concepts":[{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.663100004196167},{"id":"https://openalex.org/C162317418","wikidata":"https://www.wikidata.org/wiki/Q252857","display_name":"Transcriptome","level":4,"score":0.6313999891281128},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5927000045776367},{"id":"https://openalex.org/C2778473407","wikidata":"https://www.wikidata.org/wiki/Q1459574","display_name":"Compendium","level":2,"score":0.5773000121116638},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.5705000162124634},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5030999779701233},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.48559999465942383},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4456999897956848},{"id":"https://openalex.org/C161624437","wikidata":"https://www.wikidata.org/wiki/Q1988322","display_name":"Small molecule","level":2,"score":0.4399000108242035},{"id":"https://openalex.org/C2987395477","wikidata":"https://www.wikidata.org/wiki/Q135085","display_name":"Gene ontology","level":4,"score":0.40689998865127563},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.39800000190734863},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.36739999055862427},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3328000009059906},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.3095000088214874},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C3019060180","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automated method","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27160000801086426},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.31522","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31522","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.31522","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31522","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"perturbation":[1,183],"models":[2,157],"require":[3],"training":[4],"data":[5],"encompassing":[6],"chemical,":[7],"cellular,":[8],"and":[9,27,44,56,70,86,107,140,178],"assay":[10,50],"diversity.":[11],"Current":[12],"transcriptomic":[13,46,184],"resources":[14],"for":[15,120],"small-molecule":[16],"modeling,":[17],"however,":[18],"are":[19,166],"fragmented":[20],"across":[21,48,68,88,145,151],"technologies,":[22],"metadata":[23],"conventions,":[24],"controls,":[25],"doses,":[26],"preprocessing":[28],"pipelines.":[29],"We":[30,60,112],"introduce":[31],"Chem-PerturBridge,":[32],"a":[33,117,125],"harmonized":[34],"multi-dataset":[35],"resource":[36,63,119],"comprising":[37],"over":[38,135],"37k":[39],"compounds,":[40],"136":[41],"cellular":[42],"contexts,":[43],"1.25M":[45],"samples":[47],"eight":[49],"types,":[51],"with":[52],"standardized":[53],"identifiers,":[54],"metadata,":[55],"replicate-aware":[57],"condition-level":[58],"effects.":[59],"use":[61],"the":[62,141],"to":[64],"evaluate":[65,114],"matched-condition":[66],"agreement":[67,72,81,102,177],"datasets":[69,153],"replicate":[71],"within":[73],"datasets.":[74],"Matched":[75],"same-compound":[76],"conditions":[77],"generally":[78],"show":[79],"weak":[80],"in":[82],"fine-grained":[83],"logFC":[84,100],"rankings":[85],"magnitudes":[87],"most":[89],"dataset":[90],"pairs,":[91],"often":[92],"falling":[93],"below":[94],"same-context":[95],"different-compound":[96],"baselines.":[97,111],"In":[98],"contrast,":[99],"direction":[101],"is":[103],"substantially":[104],"more":[105],"stable":[106],"usually":[108],"exceeds":[109],"these":[110],"further":[113,154],"Chem-PerturBridge":[115,133,160,168],"as":[116],"pretraining":[118],"compound":[121],"representation":[122],"learning.":[123],"Under":[124],"compound-held-out":[126],"OP3":[127,143],"evaluation":[128,150,173],"split,":[129],"embeddings":[130],"pretrained":[131],"on":[132,159],"improve":[134],"L1000-only":[136],"embeddings,":[137],"Morgan":[138],"fingerprints,":[139],"descriptor-free":[142],"baseline":[144],"metrics.":[146],"An":[147],"extensive":[148],"molecule-holdout":[149],"11":[152],"shows":[155],"that":[156,165],"trained":[158],"outperform":[161],"or":[162],"match":[163],"those":[164],"not.":[167],"therefore":[169],"supports":[170],"both":[171],"diagnostic":[172],"of":[174,181],"cross-dataset":[175],"signature":[176],"model-oriented":[179],"reuse":[180],"heterogeneous":[182],"data.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-02T00:00:00"}
