seminario: "Comparative gene finding on highly diverse chromosome alleles", Marina Axelson-Fisk 26 April
You are welcome to the next Statistics seminar at Dept of Mathematical Sciences at Chalmers and Göteborg University. On Tuesday April 26, Marina Axelson-Fisk <http://www.math.chalmers.se/~marinaa/> will talk of: ///"Comparative gene finding on highly diverse chromosome alleles"/ / / //*About the speaker: *Marina Axelson-Fisk <http://www.math.chalmers.se/~marinaa/> is an Assc. Professor in Mathematical Statistics at Chalmers and University of Gothenburg. She works mainly within the field of Bioinformatics, with particular focus on stochastic models and algorithms for comparative genomics and cross-species gene finding. She is an associate member of the Linnaeus Centre for Marine Evolutionary Biology (CeMEB), where she is involved in the bioinformatics analysis of a number of newly sequenced Swedish coastal organisms. ** *Abstract:* With the new sequencing technologies, the number of novel genome sequences has exploded. At the same time the genome projects are hampered by the lack of homologies to the novel genome, making it difficult both to properly train genome analysis tools and to assess the results. Moreover, the faster and cheaper sequencing methods come with the cost of data quality, and sequencing and annotation errors that make it into the genome databases are propagated to new genomes, making annotation an even bigger challenge. Methods that can improve the data quality is desperately needed. Here we propose a novel use of comparative gene finding to improve the annotation in organisms with high nucleotide diversity. Comparative gene finding methods utilizes the contrast in sequence similarity between functional and non-functional regions of evolutionary related species. We show how this can be applied to chromosome pair sequences in diploid sequence data. We demonstrate the approach on the highly diverse sea orchid Balanus improvisus using SLAM, a cross-species gene finder that simultaneously annotates and aligns two homologous sequences using Generalized Pair Hidden Markov Models.* * *Feel free to spread this announcement in your network.* * * *Where*: room MVL14 or https://chalmers.zoom.us/j/62177902216 Password: 786749 ** **** *When*: Tuesday 26 April at 14.30-15.30*(Swedish time, UTC+2)*. ** -- _________________________________________________________ Umberto Picchini, Associate Professor, PhD, Docent https://umbertopicchini.github.io/ , twitter: @uPicchini
il seminario annunciato per oggi e' *cancellato e spostato* a Martedi 3 Maggio sempre alle 14.30 e con il medesimo link zoom. On 2022-04-22 08:39, Umberto Picchini wrote:
You are welcome to the next Statistics seminar at Dept of Mathematical Sciences at Chalmers and Göteborg University.
On Tuesday April 26, Marina Axelson-Fisk <http://www.math.chalmers.se/~marinaa/> will talk of:
///"Comparative gene finding on highly diverse chromosome alleles"/ / / //*About the speaker: *Marina Axelson-Fisk <http://www.math.chalmers.se/~marinaa/> is an Assc. Professor in Mathematical Statistics at Chalmers and University of Gothenburg. She works mainly within the field of Bioinformatics, with particular focus on stochastic models and algorithms for comparative genomics and cross-species gene finding. She is an associate member of the Linnaeus Centre for Marine Evolutionary Biology (CeMEB), where she is involved in the bioinformatics analysis of a number of newly sequenced Swedish coastal organisms.
** *Abstract:* With the new sequencing technologies, the number of novel genome sequences has exploded. At the same time the genome projects are hampered by the lack of homologies to the novel genome, making it difficult both to properly train genome analysis tools and to assess the results. Moreover, the faster and cheaper sequencing methods come with the cost of data quality, and sequencing and annotation errors that make it into the genome databases are propagated to new genomes, making annotation an even bigger challenge. Methods that can improve the data quality is desperately needed. Here we propose a novel use of comparative gene finding to improve the annotation in organisms with high nucleotide diversity. Comparative gene finding methods utilizes the contrast in sequence similarity between functional and non-functional regions of evolutionary related species. We show how this can be applied to chromosome pair sequences in diploid sequence data. We demonstrate the approach on the highly diverse sea orchid Balanus improvisus using SLAM, a cross-species gene finder that simultaneously annotates and aligns two homologous sequences using Generalized Pair Hidden Markov Models.* *
*Feel free to spread this announcement in your network.* * * *Where*: room MVL14 or https://chalmers.zoom.us/j/62177902216 Password: 786749 **
**** *When*: Tuesday 26 April at 14.30-15.30*(Swedish time, UTC+2)*. ** -- _________________________________________________________ Umberto Picchini, Associate Professor, PhD, Docent https://umbertopicchini.github.io/ , twitter: @uPicchini
participants (1)
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Umberto Picchini