Biomedical subjects

Nickolai Alexandrov

Publications and source records attributed to Nickolai Alexandrov.

4 recordsLinked to original sources

PubMed2004

Genome-scale gene function prediction using multiple sources of high-throughput data in yeast Saccharomyces cerevisiae.

Characterizing gene function is one of the major challenging tasks in the post-genomic era. To address this challenge, we have developed GeneFAS (Gene Function Annotation System), a new integrated probabilistic method for cellular function prediction by combining information from protein-protein interactions, protein complexes, microarray gene expression profiles, and annotations of known proteins through an integrative statistical model. Our approach is based on a novel assessment for the relationship between (1) the interaction/correlation of two proteins' high-throughput data and (2) their functional relationship in terms of their Gene Ontology (GO) hierarchy. We have developed a Web server for the predictions. We have applied our method to yeast Saccharomyces cerevisiae and predicted functions for 1548 out of 2472 unannotated proteins.

Automation↗

PubMed2003

PDP: protein domain parser.

UNLABELLED: We have developed a program for automatic identification of domains in protein three-dimensional structures. Performance of the program was assessed by three different benchmarks: (i) by comparison with the expert-curated SCOP database of structural domains; (ii) by comparison with a collection of manual domain assignments; and (iii) by comparison with a set of 55 proteins, frequently used as a benchmark for automatic domain assignment. In all these benchmarks PDP identified domains correctly in more than 80% of proteins. AVAILABILITY: http://123d.ncifcrf.gov/.

Algorithms↗

PubMed2003

Skew in CG content near the transcription start site in Arabidopsis thaliana.

We have discovered a novel statistical feature of Arabidopsis thaliana genome that remarkably correlates with a position of transcription start site--CG skew peak. We hypothesize that the phenomenon can be explained by the higher mutability of unprotected cytosines.

Arabidopsis↗

PubMed2002

Full-length messenger RNA sequences greatly improve genome annotation.

BACKGROUND: Annotation of eukaryotic genomes is a complex endeavor that requires the integration of evidence from multiple, often contradictory, sources. With the ever-increasing amount of genome sequence data now available, methods for accurate identification of large numbers of genes have become urgently needed. In an effort to create a set of very high-quality gene models, we used the sequence of 5,000 full-length gene transcripts from Arabidopsis to re-annotate its genome. We have mapped these transcripts to their exact chromosomal locations and, using alignment programs, have created gene models that provide a reference set for this organism. RESULTS: Approximately 35% of the transcripts indicated that previously annotated genes needed modification, and 5% of the transcripts represented newly discovered genes. We also discovered that multiple transcription initiation sites appear to be much more common than previously known, and we report numerous cases of alternative mRNA splicing. We include a comparison of different alignment software and an analysis of how the transcript data improved the previously published annotation. CONCLUSIONS: Our results demonstrate that sequencing of large numbers of full-length transcripts followed by computational mapping greatly improves identification of the complete exon structures of eukaryotic genes. In addition, we are able to find numerous introns in the untranslated regions of the genes.

Alternative Splicing↗