PubMed Health⌕ Search

Biomedical subjects

Dennis Shasha

Publications and source records attributed to Dennis Shasha.

3 recordsLinked to original sources

In vitro and in silico cloning of Xenopus laevis SOD2 cDNA and its phylogenetic analysis.

By using the methodology of both wet and dry biology (i.e., RT-PCR and cycle sequencing, and biocomputational technology, respectively) and the data obtained through the Genome Projects, we have cloned Xenopus laevis SOD2 (MnSOD) cDNA and determined its nucleotide sequence. These data and the deduced protein primary structure were compared with all the other SOD2 nucleotide and amino acid sequences from eukaryotes and prokaryotes, published in public databases. The analysis was performed by using both Clustal W, a well known and widely used program for sequence analysis, and AntiClustAl, a new algorithm recently created and implemented by our group. Our results demonstrate a very high conservation of the enzyme amino acid sequence during evolution, which proves a close structure-function relationship. This is to be expected for very ancient molecules endowed with critical biological functions, performed through a specific structural organization. The nucleotide sequence conservation is less pronounced: this too was foreseeable, due to neutral mutations and to the species-specific codon usage. The data obtained by using AntiClustAl are comparable with those produced with Clustal W, which validates this algorithm as an important new tool for biocomputational analysis. Finally, it is noteworthy that evolutionary trees, drawn by using all the available data on SOD2 nucleotide sequences and amino acid and either Clustal W or AntiClustAl, are comparable to those obtained through phylogenetic analysis based on fossil records.

Amino Acid Sequence↗

MetricMap: an embedding technique for processing distance-based queries in metric spaces.

In this paper, we present an embedding technique, called MetricMap, which is capable of estimating distances in a pseudometric space. Given a database of objects and a distance function for the objects, which is a pseudometric, we map the objects to vectors in a pseudo-Euclidean space with a reasonably low dimension while preserving the distance between two objects approximately. Such an embedding technique can be used as an approximate oracle to process a broad class of distance-based queries. It is also adaptable to data mining applications such as data clustering and classification. We present the theory underlying MetricMap and conduct experiments to compare MetricMap with other methods including MVP-tree and M-tree in processing the distance-based queries. Experimental results on both protein and RNA data show the good performance and the superiority of MetricMap over the other methods.

Algorithms↗

Trait-to-gene: a computational method for predicting the function of uncharacterized genes.

The function of unknown genes is often inferred from comparisons to well-characterized homologs. In this paper, we show that, even if all of the homologs of a gene are unannotated, its function may be deduced through phylogenetic profiling. We have designed a series of algorithms that make functional predictions of genes based on orthology and set theory, but our approach to predicting gene function requires no previous knowledge of homolog function. With this technique, we successfully identified 94% of the clusters of orthologous groups that are known to be involved in flagella development or function. As a test, we removed the function of three putative flagellar genes that had been previously uncharacterized in Bacillus subtilis. We observed a motility phenotype for two of these three genes. Thus, these algorithms allow for high-throughput functional prediction of genes beyond that provided by simple orthology-based annotation endeavors.

Algorithms↗