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Biomedical subjects

Kuan Chang

Publications and source records attributed to Kuan Chang.

3 recordsLinked to original sources

Correcting BLAST e-values for low-complexity segments.

The statistical estimates of BLAST and PSI-BLAST are of extreme importance to determine the biological relevance of sequence matches. While being very effective in evaluating most matches, these estimates usually overestimate the significance of matches in the presence of low complexity segments. In this paper, we present a model, based on divergence measures and statistics of the alignment structure, that corrects BLAST e-values for low complexity sequences without filtering or excluding them and generates scores that are more effective in distinguishing true similarities from chance similarities. We evaluate our method and compare it to other known methods using the Gene Ontology (GO) knowledge resource as a benchmark. Various performance measures, including ROC analysis, indicate that the new model improves upon the state of the art. The program is available at biozon.org/ftp/ and www.cs.technion.ac.il/ approximately itaish/lowcomp/.

Amino Acid Sequence↗

Gramene: a resource for comparative grass genomics.

Gramene (http://www.gramene.org) is a comparative genome mapping database for grasses and a community resource for rice. Rice, in addition to being an economically important crop, is also a model monocot for understanding other agronomically important grass genomes. Gramene replaces the existing AceDB database 'RiceGenes' with a relational database based on Oracle. Gramene provides curated and integrative information about maps, sequence, genes, genetic markers, mutants, QTLs, controlled vocabularies and publications. Its aims are to use the rice genetic, physical and sequence maps as fundamental organizing units, to provide a common denominator for moving from one crop grass to another and is to serve as a portal for interconnecting with other web-based crop grass resources. This paper describes the initial steps we have taken towards realizing these goals.

Chromosome Mapping↗

Gramene, a tool for grass genomics.

Gramene (http://www.gramene.org) is a comparative genome mapping database for grasses and a community resource for rice (Oryza sativa). It combines a semi-automatically generated database of cereal genomic and expressed sequence tag sequences, genetic maps, map relations, and publications, with a curated database of rice mutants (genes and alleles), molecular markers, and proteins. Gramene curators read and extract detailed information from published sources, summarize that information in a structured format, and establish links to related objects both inside and outside the database, providing seamless connections between independent sources of information. Genetic, physical, and sequence-based maps of rice serve as the fundamental organizing units and provide a common denominator for moving across species and genera within the grass family. Comparative maps of rice, maize (Zea mays), sorghum (Sorghum bicolor), barley (Hordeum vulgare), wheat (Triticum aestivum), and oat (Avena sativa) are anchored by a set of curated correspondences. In addition to sequence-based mappings found in comparative maps and rice genome displays, Gramene makes extensive use of controlled vocabularies to describe specific biological attributes in ways that permit users to query those domains and make comparisons across taxonomic groups. Proteins are annotated for functional significance using gene ontology terms that have been adopted by numerous model species databases. Genetic variants including phenotypes are annotated using plant ontology terms common to all plants and trait ontology terms that are specific to rice. In this paper, we present a brief overview of the search tools available to the plant research community in Gramene.

Avena↗