{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/29681"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/29681","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Development of gene-finding algorithms for fungal genomes : dealing with small datasets and leveraging comparative genomics","abstract":"A computer program called FUNSCAN was developed which identifies protein coding regions in fungal genomes. Gene structural and compositional properties are modeled using a Hidden Markov Model. Separate training and testing sets for FUNSCAN were obtained by aligning cDNAs from an organism to their genomic loci, generating a 'gold standard' set of annotated genes. The performance of FUNSCAN is competitive with other computer programs design to identify protein coding regions in fungal genomes. A technique called 'Training Set Augmentation' is described which can be used to train FUNSCAN when only a small training set of genes is available. Techniques that combine alignment algorithms with FUNSCAN to identify novel genes are also discussed and explored.","abstract_html":"A computer program called FUNSCAN was developed which identifies protein coding regions in fungal genomes. Gene structural and compositional properties are modeled using a Hidden Markov Model. Separate training and testing sets for FUNSCAN were obtained by aligning cDNAs from an organism to their genomic loci, generating a 'gold standard' set of annotated genes. The performance of FUNSCAN is competitive with other computer programs design to identify protein coding regions in fungal genomes. A technique called 'Training Set Augmentation' is described which can be used to train FUNSCAN when only a small training set of genes is available. Techniques that combine alignment algorithms with FUNSCAN to identify novel genes are also discussed and explored.","abstract_has_math":false,"creators":["Lazarovici, Allan, 1979-"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Christopher Burge."],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003","date_published":"2003","updated_at":"2026-07-22T22:22:10Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 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