Biomedical subjects

Victor Kunin

Publications and source records attributed to Victor Kunin.

7 recordsLinked to original sources

PubMed2003

Protein families and TRIBES in genome sequence space.

Accurate detection of protein families allows assignment of protein function and the analysis of functional diversity in complete genomes. Recently, we presented a novel algorithm called TribeMCL for the detection of protein families that is both accurate and efficient. This method allows family analysis to be carried out on a very large scale. Using TribeMCL, we have generated a resource called TRIBES that contains protein family information, comprising annotations, protein sequence alignments and phylogenetic distributions describing 311 257 proteins from 83 completely sequenced genomes. The analysis of at least 60 934 detected protein families reveals that, with the essential families excluded, paralogy levels are similar between prokaryotes, irrespective of genome size. The number of essential families is estimated to be between 366 and 426. We also show that the currently known space of protein families is scale free and discuss the implications of this distribution. In addition, we show that smaller families are often formed by shorter proteins and discuss the reasons for this intriguing pattern. Finally, we analyse the functional diversity of protein families in entire genome sequences. The TRIBES protein family resource is accessible at http://www.ebi.ac.uk/research/cgg/tribes/.

Algorithms↗

PubMed2003

COmplete GENome Tracking (COGENT): a flexible data environment for computational genomics.

SUMMARY: We present a database of fully sequenced and published genomes to facilitate the re-distribution of data and ensure reproducibility of results in the field of computational genomics. For its design we have implemented an extremely simple yet powerful schema to allow linking of genome sequence data to other resources. AVAILABILITY: http://maine.ebi.ac.uk:8000/services/cogent/

Computational Biology↗

PubMed2003

GeneTRACE-reconstruction of gene content of ancestral species.

While current computational methods allow the reconstruction of individual ancestral protein sequences, reconstruction of complete gene content of ancestral species is not yet an established task. In this paper, we describe GENETRACE, an efficient linear-time algorithm that allows the reconstruction of evolutionary history of individual protein families as well as the complete gene content of ancestral species. The performance of the method was validated with a simulated evolution program called SimulEv. Our results indicate that given a set of correct phylogenetic profiles and a correct species tree, ancestral gene content can be reconstructed with sensitivity and selectivity of more than 90%. SimulEv simulations were also used to evaluate performance of the reconstruction of gene content-based phylogenetic trees, suggesting that these trees may be accurate at the terminal branches but suffer from long branch attraction near the root of the tree.

Algorithms↗

PubMed2003

Beyond 100 genomes.

By the end of 2002, we witnessed the landmark submission of the 100th complete genome sequence in the databases. An overview of these genomes reveals certain interesting trends and provides valuable insights into possible future developments.

Animals↗

PubMed2003

Myriads of protein families, and still counting.

From the historical record of genome sequencing, we show that the rate of discovery of new families has remained constant over time, indicating that our knowledge of sequence space is far from complete.

Animals↗

PubMed2003

Classification schemes for protein structure and function.

We examine the structural and functional classifications of the protein universe, providing an overview of the existing classification schemes, their features and inter-relationships. We argue that a unified scheme should be based on a natural classification approach and that more comparative analyses of the present schemes are required both to understand their limitations and to help delimit the number of known protein folds and their corresponding functional roles in cells.

Animals↗

PubMed2003

The balance of driving forces during genome evolution in prokaryotes.

Genomes are shaped by evolutionary processes such as gene genesis, horizontal gene transfer (HGT), and gene loss. To quantify the relative contributions of these processes, we analyze the distribution of 12,762 protein families on a phylogenetic tree, derived from entire genomes of 41 Bacteria and 10 Archaea. We show that gene loss is the most important factor in shaping genome content, being up to three times more frequent than HGT, followed by gene genesis, which may contribute up to twice as many genes as HGT. We suggest that gene gain and gene loss in prokaryotes are balanced; thus, on average, prokaryotic genome size is kept constant. Despite the importance of HGT, our results indicate that the majority of protein families have only been transmitted by vertical inheritance. To test our method, we present a study of strain-specific genes of Helicobacter pylori, and demonstrate correct predictions of gene loss and HGT for at least 81% of validated cases. This approach indicates that it is possible to trace genome content history and quantify the factors that shape contemporary prokaryotic genomes.

Archaeal Proteins↗