{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T14:24:42Z","timestamp":1788531882467,"version":"build-2803163510"},"reference-count":97,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:00:00Z","timestamp":1788480000000},"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":["32560680"],"award-info":[{"award-number":["32560680"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["32560680"],"award-info":[{"award-number":["32560680"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Reserve Talents Project for Yunnan Young and Middle-aged Academic and Technical Leaders","award":["202105AC160037"],"award-info":[{"award-number":["202105AC160037"]}]},{"name":"Yunnan Fundamental Research Projects","award":["202401AT070240"],"award-info":[{"award-number":["202401AT070240"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Insects"],"abstract":"<jats:p>Genome-scale searches for insect olfactory genes are vulnerable to rapid receptor divergence, tandem duplication, fragmented gene models, circular labels, and evolutionary leakage between training and test data. Sequence foundation models trained on DNA or proteins may extend homology-based annotation, but available evidence does not support their use as autonomous annotators or direct predictors of sensory function. This critical review organizes the problem around annotation failures rather than model catalogues. We distinguish six inference levels, from candidate locus detection to organism-level function, and define task-specific high-confidence reference criteria. We also propose a benchmark using biological hard negatives, sequence-cluster and taxonomic holdouts, conventional baselines, calibration, abstention, and workload-aware retrieval metrics. Evidence integration is defined operationally as a pipeline that retains model scores alongside similarity, domains, topology, phylogeny, expression, and assay evidence, without promoting a weak signal to a stronger biological claim. A published ESM-2-supported analysis of remote insect chemoreceptor homology illustrates both the potential and the current evidence boundary. A convincing benefit will require an incremental gain over transparent baselines under frozen biologically realistic splits, with reliable uncertainty and a clear route from ambiguous predictions to review or experiment.<\/jats:p>","DOI":"10.3390\/insects17090928","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T13:50:44Z","timestamp":1788529844000},"page":"928","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating Sequence Foundation Models for Insect Olfactory Gene Discovery: Failure Modes, Evidence Standards, and a Benchmark Agenda"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-8128-0186","authenticated-orcid":false,"given":"Huiqin","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming 650201, China"},{"name":"College of Plant Protection, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2783-0701","authenticated-orcid":false,"given":"Dian","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Sanqi Medicine and Pharmacy, Wenshan University, Wenshan 663000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Pu","sequence":"additional","affiliation":[{"name":"School of Continuing Education, Honghe University, Mengzi 661199, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoxing","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming 650201, China"},{"name":"College of Plant Protection, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7245-4509","authenticated-orcid":false,"given":"Chun","family":"Xiao","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming 650201, China"},{"name":"College of Plant Protection, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming 650201, China"},{"name":"College of Plant Protection, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7224-3306","authenticated-orcid":false,"given":"Junfu","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming 650201, China"},{"name":"College of Plant Protection, Yunnan Agricultural University, Kunming 650201, China"},{"name":"College of Big Data, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.cell.2008.12.001","article-title":"Variant ionotropic glutamate receptors as chemosensory receptors in Drosophila","volume":"136","author":"Benton","year":"2009","journal-title":"Cell"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1016\/j.neuron.2011.11.003","article-title":"Evolution of insect olfaction","volume":"72","author":"Hansson","year":"2011","journal-title":"Neuron"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1146\/annurev-ento-120811-153635","article-title":"Odorant reception in insects: Roles of receptors, binding proteins, and degrading enzymes","volume":"58","author":"Leal","year":"2013","journal-title":"Annu. Rev. Entomol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1016\/j.ibmb.2013.02.007","article-title":"Ionotropic receptors (IRs): Chemosensory ionotropic glutamate receptors in Drosophila and beyond","volume":"43","author":"Rytz","year":"2013","journal-title":"Insect Biochem. Mol. Biol."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Croset, V., Rytz, R., Cummins, S.F., Budd, A., Brawand, D., Kaessmann, H., Gibson, T.J., and Benton, R. (2010). Ancient protostome origin of chemosensory ionotropic glutamate receptors and the evolution of insect taste and olfaction. PLoS Genet., 6.","DOI":"10.1371\/journal.pgen.1001064"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1101\/gr.5057506","article-title":"The chemoreceptor superfamily in the honey bee, Apis mellifera: Expansion of the odorant, but not gustatory, receptor family","volume":"16","author":"Robertson","year":"2006","journal-title":"Genome Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1093\/gbe\/evr033","article-title":"Comparative genomics of the odorant-binding and chemosensory protein gene families across the Arthropoda: Origin and evolutionary history of the chemosensory system","volume":"3","author":"Vieira","year":"2011","journal-title":"Genome Biol. Evol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4055","DOI":"10.1038\/s41598-019-40640-4","article-title":"Use of machine learning to identify novel, behaviorally active antagonists of the insect odorant receptor co-receptor Orco subunit","volume":"9","author":"Kepchia","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_9","first-page":"RP95532","article-title":"Machine learning based modelling of human and insect olfaction screens millions of compounds to identify pleasant smelling insect repellents","volume":"13","author":"Kowalewski","year":"2024","journal-title":"eLife"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/S0022-2836(05)80360-2","article-title":"Basic local alignment search tool","volume":"215","author":"Altschul","year":"1990","journal-title":"J. Mol. Biol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Eddy, S.R. (2011). Accelerated profile HMM searches. PLoS Comput. Biol., 7.","DOI":"10.1371\/journal.pcbi.1002195"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"D344","DOI":"10.1093\/nar\/gkaa977","article-title":"The InterPro protein families and domains database: 20 years on","volume":"49","author":"Blum","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"D412","DOI":"10.1093\/nar\/gkaa913","article-title":"Pfam: The protein families database in 2021","volume":"49","author":"Mistry","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"D418","DOI":"10.1093\/nar\/gkac993","article-title":"InterPro in 2022","volume":"51","author":"Blum","year":"2023","journal-title":"Nucleic Acids Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1038\/nbt.3988","article-title":"MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets","volume":"35","author":"Steinegger","year":"2017","journal-title":"Nat. Biotechnol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1093\/molbev\/mst010","article-title":"MAFFT multiple sequence alignment software version 7: Improvements in performance and usability","volume":"30","author":"Katoh","year":"2013","journal-title":"Mol. Biol. Evol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1530","DOI":"10.1093\/molbev\/msaa015","article-title":"IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era","volume":"37","author":"Minh","year":"2020","journal-title":"Mol. Biol. Evol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1038\/s41587-021-01156-3","article-title":"SignalP 6.0 predicts all five types of signal peptides using protein language models","volume":"40","author":"Teufel","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1038\/s41587-023-01773-0","article-title":"Fast and accurate protein structure search with Foldseek","volume":"42","author":"Kim","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1038\/s41592-021-01101-x","article-title":"Sensitive protein alignments at tree-of-life scale using DIAMOND","volume":"18","author":"Buchfink","year":"2021","journal-title":"Nat. Methods"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5023","DOI":"10.1016\/j.cub.2023.10.008","article-title":"Remote homolog detection places insect chemoreceptors in a cryptic protein superfamily spanning the tree of life","volume":"33","author":"Himmel","year":"2023","journal-title":"Curr. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e2016239118","DOI":"10.1073\/pnas.2016239118","article-title":"Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences","volume":"118","author":"Rives","year":"2021","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7112","DOI":"10.1109\/TPAMI.2021.3095381","article-title":"ProtTrans: Toward understanding the language of life through self-supervised learning","volume":"44","author":"Elnaggar","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1126\/science.ade2574","article-title":"Evolutionary-scale prediction of atomic-level protein structure with a language model","volume":"379","author":"Lin","year":"2023","journal-title":"Science"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2112","DOI":"10.1093\/bioinformatics\/btab083","article-title":"DNABERT: Pre-trained bidirectional encoder representations from transformers model for DNA-language in genome","volume":"37","author":"Ji","year":"2021","journal-title":"Bioinformatics"},{"key":"ref_26","unstructured":"Zhou, Z., Ji, Y., Li, W., Dutta, P., Davuluri, R.V., and Liu, H. (2024). DNABERT-2: Efficient foundation model and benchmark for multi-species genome. International Conference on Learning Representations. arXiv."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1038\/s41592-024-02523-z","article-title":"Nucleotide Transformer: Building and evaluating robust foundation models for human genomics","volume":"22","author":"Gonzalez","year":"2025","journal-title":"Nat. Methods"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"43177","DOI":"10.52202\/075280-1872","article-title":"HyenaDNA: Long-range genomic sequence modeling at single nucleotide resolution","volume":"36","author":"Nguyen","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"eado9336","DOI":"10.1126\/science.ado9336","article-title":"Sequence modeling and design from molecular to genome scale with Evo","volume":"386","author":"Nguyen","year":"2024","journal-title":"Science"},{"key":"ref_30","unstructured":"Gu, A., and Dao, T. (2023). Mamba: Linear-time sequence modeling with selective state spaces. arXiv."},{"key":"ref_31","first-page":"43632","article-title":"Caduceus: Bi-directional equivariant long-range DNA sequence modeling","volume":"Volume 235","author":"Schiff","year":"2024","journal-title":"Proceedings of the 41st International Conference on Machine Learning, Proceedings of Machine Learning Research"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"gkae1310","DOI":"10.1093\/nar\/gkae1310","article-title":"GENA-LM: A family of open-source foundational DNA language models for long sequences","volume":"53","author":"Fishman","year":"2025","journal-title":"Nucleic Acids Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1038\/s41586-026-10176-5","article-title":"Genome modelling and design across all domains of life with Evo 2","volume":"652","author":"Brixi","year":"2026","journal-title":"Nature"},{"key":"ref_34","unstructured":"Marin, F.I., Teufel, F., Horlacher, M., Madsen, D., Pultz, D., Winther, O., and Boomsma, W. (2024, January 7\u201311). BEND: Benchmarking DNA language models on biologically meaningful tasks. Proceedings of the International Conference on Learning Representations, Vienna, Austria."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"10780","DOI":"10.1038\/s41467-025-65823-8","article-title":"Benchmarking DNA foundation models for genomic and genetic tasks","volume":"16","author":"Feng","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_36","first-page":"9689","article-title":"Evaluating protein transfer learning with TAPE","volume":"32","author":"Rao","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1038\/s41576-021-00434-9","article-title":"Navigating the pitfalls of applying machine learning in genomics","volume":"23","author":"Whalen","year":"2022","journal-title":"Nat. Rev. Genet."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1186\/s13059-025-03674-8","article-title":"Evaluating the representational power of pre-trained DNA language models for regulatory genomics","volume":"26","author":"Tang","year":"2025","journal-title":"Genome Biol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/S0896-6273(00)81093-4","article-title":"A novel family of divergent seven-transmembrane proteins: Candidate odorant receptors in Drosophila","volume":"22","author":"Clyne","year":"1999","journal-title":"Neuron"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1006\/geno.1999.5894","article-title":"Identification of candidate Drosophila olfactory receptors from genomic DNA sequence","volume":"60","author":"Gao","year":"1999","journal-title":"Genomics"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1016\/S0092-8674(00)80582-6","article-title":"A spatial map of olfactory receptor expression in the Drosophila antenna","volume":"96","author":"Vosshall","year":"1999","journal-title":"Cell"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1016\/j.neuron.2004.08.019","article-title":"Or83b encodes a broadly expressed odorant receptor essential for Drosophila olfaction","volume":"43","author":"Larsson","year":"2004","journal-title":"Neuron"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1038\/nature06850","article-title":"Insect olfactory receptors are heteromeric ligand-gated ion channels","volume":"452","author":"Sato","year":"2008","journal-title":"Nature"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1038\/nature06861","article-title":"Drosophila odorant receptors are both ligand-gated and cyclic-nucleotide-activated cation channels","volume":"452","author":"Wicher","year":"2008","journal-title":"Nature"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1038\/s41586-018-0420-8","article-title":"Cryo-EM structure of the insect olfactory receptor Orco","volume":"560","author":"Butterwick","year":"2018","journal-title":"Nature"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1038\/s41586-021-03794-8","article-title":"The structural basis of odorant recognition in insect olfactory receptors","volume":"597","author":"Yedlin","year":"2021","journal-title":"Nature"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.1126\/science.adn6881","article-title":"Structural basis for odorant recognition of the insect odorant receptor OR-Orco heterocomplex","volume":"384","author":"Wang","year":"2024","journal-title":"Science"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"e02115","DOI":"10.7554\/eLife.02115","article-title":"Evolution of insect olfactory receptors","volume":"3","author":"Missbach","year":"2014","journal-title":"eLife"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Pelosi, P., Iovinella, I., Felicioli, A., and Dani, F.R. (2014). Soluble proteins of chemical communication: An overview across arthropods. Front. Physiol., 5.","DOI":"10.3389\/fphys.2014.00320"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1038\/nature06328","article-title":"An essential role for a CD36-related receptor in pheromone detection in Drosophila","volume":"450","author":"Benton","year":"2007","journal-title":"Nature"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"10996","DOI":"10.1073\/pnas.0803309105","article-title":"SNMP is a signaling component required for pheromone sensitivity in Drosophila","volume":"105","author":"Jin","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1111\/1744-7917.12816","article-title":"Characterization of sensory neuron membrane proteins (SNMPs) in cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae)","volume":"28","author":"Xu","year":"2021","journal-title":"Insect Sci."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Chertemps, T., and Ma\u00efb\u00e8che, M. (2021). Odor degrading enzymes and signal termination. Insect Pheromone Biochemistry and Molecular Biology, Academic Press. [2nd ed.].","DOI":"10.1016\/B978-0-12-819628-1.00019-5"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.ibmb.2014.07.003","article-title":"Identification of candidate odorant degrading gene\/enzyme systems in the antennal transcriptome of Drosophila melanogaster","volume":"53","author":"Younus","year":"2014","journal-title":"Insect Biochem. Mol. Biol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1146\/annurev.genet.39.073003.112240","article-title":"Concerted and birth-and-death evolution of multigene families","volume":"39","author":"Nei","year":"2005","journal-title":"Annu. Rev. Genet."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1038\/hdy.2009.55","article-title":"Molecular evolution of the major chemosensory gene families in insects","volume":"103","author":"Vieira","year":"2009","journal-title":"Heredity"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s00239-014-9633-0","article-title":"Molecular evolution of the odorant and gustatory receptor genes in lepidopteran insects: Implications for their adaptation and speciation","volume":"79","author":"Engsontia","year":"2014","journal-title":"J. Mol. Evol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"14091","DOI":"10.1073\/pnas.1610800113","article-title":"Transcriptomics and neuroanatomy of the clonal raider ant implicate an expanded clade of odorant receptors in chemical communication","volume":"113","author":"McKenzie","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Zhou, X., Slone, J.D., Rokas, A., Berger, S.L., Liebig, J., Ray, A., Reinberg, D., and Zwiebel, L.J. (2012). Phylogenetic and transcriptomic analysis of chemosensory receptors in a pair of divergent ant species reveals sex-specific signatures of odor coding. PLoS Genet., 8.","DOI":"10.1371\/journal.pgen.1002930"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1038\/s41586-020-2073-7","article-title":"Olfactory receptor and circuit evolution promote host specialization","volume":"579","author":"Auer","year":"2020","journal-title":"Nature"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Dallago, C., Mou, J., Johnston, K.E., Wittmann, B.J., Bhattacharya, N., Goldman, S., Madani, A., and Yang, K.K. (2021). FLIP: Benchmark tasks in fitness landscape inference for proteins. bioRxiv.","DOI":"10.1101\/2021.11.09.467890"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"64331","DOI":"10.52202\/075280-2810","article-title":"ProteinGym: Large-scale benchmarks for protein fitness prediction and design","volume":"36","author":"Notin","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"4647","DOI":"10.1093\/molbev\/msab199","article-title":"BUSCO update: Novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes","volume":"38","author":"Manni","year":"2021","journal-title":"Mol. Biol. Evol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1101\/gr.278090.123","article-title":"BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS, and TSEBRA","volume":"34","author":"Gabriel","year":"2024","journal-title":"Genome Res."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.1016\/j.cub.2005.07.034","article-title":"Molecular, anatomical, and functional organization of the Drosophila olfactory system","volume":"15","author":"Couto","year":"2005","journal-title":"Curr. Biol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1548","DOI":"10.1016\/j.cub.2005.07.066","article-title":"Genetic and functional subdivision of the Drosophila antennal lobe","volume":"15","author":"Fishilevich","year":"2005","journal-title":"Curr. Biol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.cell.2006.01.050","article-title":"Coding of odors by a receptor repertoire","volume":"125","author":"Hallem","year":"2006","journal-title":"Cell"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/nature08834","article-title":"Odorant reception in the malaria mosquito Anopheles gambiae","volume":"464","author":"Carey","year":"2010","journal-title":"Nature"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Matthews, B.J., McBride, C.S., DeGennaro, M., Despo, O., and Vosshall, L.B. (2016). The neurotranscriptome of the Aedes aegypti mosquito. BMC Genom., 17.","DOI":"10.1186\/s12864-015-2239-0"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"8260","DOI":"10.1073\/pnas.1302562110","article-title":"Blood meal-induced changes to antennal transcriptome profiles reveal shifts in odor sensitivities in Anopheles gambiae","volume":"110","author":"Rinker","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"He, W., Meng, H., Zhang, Y., Zhang, G., Zhi, M., Li, G., and Chen, J. (2024). Identification of candidate chemosensory genes in the antennal transcriptome of Monolepta signata. PLoS ONE, 19.","DOI":"10.1371\/journal.pone.0301177"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1093\/jisesa\/iead023","article-title":"Identification and sex-specific expression of chemosensory genes in the antennal transcriptomes of Pachyrhinus yasumatsui (Coleoptera: Curculionidae)","volume":"23","author":"Hong","year":"2023","journal-title":"J. Insect Sci."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Wang, J.J., Ma, C., Yue, Y., Yang, J., Chen, L.X., Wang, Y.T., Zhao, C.C., Gao, X., Chen, H.S., and Ma, W.H. (2024). Identification of candidate chemosensory genes in Bactrocera cucurbitae based on antennal transcriptome analysis. Front. Physiol., 15.","DOI":"10.3389\/fphys.2024.1354530"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Wu, Z.R., Fan, J.T., Tong, N., Guo, J.M., Li, Y., Lu, M., and Liu, X.L. (2022). Transcriptome analysis and identification of chemosensory genes in the larvae of Plagiodera versicolora. BMC Genom., 23.","DOI":"10.1186\/s12864-022-09079-2"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1093\/jisesa\/ieac056","article-title":"Analysis of the antennal transcriptome and identification of tissue-specific expression of olfactory-related genes in Micromelalopha troglodyta (Lepidoptera: Notodontidae)","volume":"22","author":"Zhang","year":"2022","journal-title":"J. Insect Sci."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Zhao, S.H., Yue, Y., Gao, Q., Yu, R.T., Yang, Z.H., Zhou, N., and Xu, G.L. (2025). Identification and expression profiles of chemosensory genes in the antennal transcriptome of Protaetia brevitarsis (Coleoptera: Scarabaeidae). Insects, 16.","DOI":"10.3390\/insects16060607"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1111\/1744-7917.13162","article-title":"iORbase: A database for the prediction of the structures and functions of insect olfactory receptors","volume":"30","author":"Li","year":"2023","journal-title":"Insect Sci."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"i5K Consortium (2013). The i5K Initiative: Advancing arthropod genomics for knowledge, human health, agriculture, and the environment. J. Hered., 104, 595\u2013600.","DOI":"10.1093\/jhered\/est050"},{"key":"ref_79","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume":"1","author":"Devlin","year":"2019","journal-title":"Proc. NAACL-HLT"},{"key":"ref_80","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., and Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems. arXiv."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"9392","DOI":"10.1038\/s41467-024-53759-4","article-title":"A long-context language model for deciphering and generating bacteriophage genomes","volume":"15","author":"Shao","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_82","first-page":"1715","article-title":"Neural machine translation of rare words with subword units","volume":"1","author":"Sennrich","year":"2016","journal-title":"Proc. ACL"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1196","DOI":"10.1038\/s41592-021-01252-x","article-title":"Effective gene expression prediction from sequence by integrating long-range interactions","volume":"18","author":"Avsec","year":"2021","journal-title":"Nat. Methods"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"932","DOI":"10.1038\/s41587-021-01179-w","article-title":"Using deep learning to annotate the protein universe","volume":"40","author":"Bileschi","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"ref_85","unstructured":"Hu, E.J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W. (2021). LoRA: Low-rank adaptation of large language models. International Conference on Learning Representations. arXiv."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1038\/nature05466","article-title":"Two chemosensory receptors together mediate carbon dioxide detection in Drosophila","volume":"445","author":"Jones","year":"2007","journal-title":"Nature"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"3574","DOI":"10.1073\/pnas.0700079104","article-title":"The molecular basis of CO2 reception in Drosophila","volume":"104","author":"Kwon","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1122","DOI":"10.1038\/s41592-021-01205-4","article-title":"DOME: Recommendations for supervised machine learning validation in biology","volume":"18","author":"Walsh","year":"2021","journal-title":"Nat. Methods"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"vbag054","DOI":"10.1093\/bioadv\/vbag054","article-title":"BarcodeBERT: Transformers for biodiversity analyses","volume":"6","author":"Sadjadi","year":"2026","journal-title":"Bioinform. Adv."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"2301","DOI":"10.1038\/s41592-025-02881-2","article-title":"Annotating the genome at single-nucleotide resolution with DNA foundation models","volume":"22","author":"Richard","year":"2025","journal-title":"Nat. Methods"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1038\/s42256-025-01088-6","article-title":"Boosting the predictive power of protein representations with a corpus of text annotations","volume":"7","author":"Duan","year":"2025","journal-title":"Nat. Mach. Intell."},{"key":"ref_92","first-page":"13991","article-title":"Can you trust your model\u2019s uncertainty? Evaluating predictive uncertainty under dataset shift","volume":"32","author":"Ovadia","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.neuroimage.2017.06.061","article-title":"Cross-validation failure: Small sample sizes lead to large error bars","volume":"180","author":"Varoquaux","year":"2018","journal-title":"NeuroImage"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1111\/ecog.02881","article-title":"Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure","volume":"40","author":"Roberts","year":"2017","journal-title":"Ecography"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2","article-title":"Verification of forecasts expressed in terms of probability","volume":"78","author":"Brier","year":"1950","journal-title":"Mon. Weather Rev."},{"key":"ref_96","first-page":"1321","article-title":"On calibration of modern neural networks","volume":"Volume 70","author":"Guo","year":"2017","journal-title":"Proceedings of the 34th International Conference on Machine Learning"},{"key":"ref_97","first-page":"4878","article-title":"Selective classification for deep neural networks","volume":"30","author":"Geifman","year":"2017","journal-title":"Adv. Neural Inf. Process. 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