Search PubMed⌕ Search

Biomedical subjects

Edward S C Shih

Publications and source records attributed to Edward S C Shih.

3 recordsLinked to original sources

Alternative alignments from comparison of protein structures.

Comparison of two protein structures often results in not only a global alignment but also a number of distinct local alignments; the latter, referred to as alternative alignments, are however usually ignored in existing protein structure comparison analyses. Here, we used a novel method of protein structure comparison to extensively identify and characterize the alternative alignments obtained for structure pairs of a fold classification database. We showed that all alternative alignments can be classified into one of just a few types, and with which illustrated the potential of using alternative alignments to identify recurring protein substructures, including the internal structural repeats of a protein. Furthermore, we showed that among the alternative alignments obtained, permuted alignments, which included both circular and scrambled permutations, are as prevalent as topological alignments. These results demonstrated that the so far largely unattended alternative alignments of protein structures have implications and applications for research of protein classification and evolution.

Databases, Protein↗

Protein structure comparison by probability-based matching of secondary structure elements.

MOTIVATION: Protein structure comparison (PSC) has been used widely in studies of structural and functional genomics. However, PSC is computationally expensive and as a result almost all of the PSC methods currently in use look only for the optimal alignment and ignore many alternative alignments that are statistically significant and that may provide insight into protein evolution or folding. RESULTS: We have developed a new PSC method with efficiency to detect potentially viable alternative alignments in all-against-all database comparisons. The efficiency of the new PSC method derives from the ability to directly home in on a limited number of viable and ranked alignment solutions based on intuitively derived SSE (secondary structure element)-matching probabilities.

Algorithms↗

Single nucleotide polymorphism mapping using genome-wide unique sequences.

As more and more genomic DNAs are sequenced to characterize human genetic variations, the demand for a very fast and accurate method to genomically position these DNA sequences is high. We have developed a new mapping method that does not require sequence alignment. In this method, we first identified DNA fragments of 15 bp in length that are unique in the human genome and then used them to position single nucleotide polymorphism (SNP) sequences. By use of four desktop personal computers with AMD K7 (1 GHz) processors, our new method mapped more than 1.6 million SNP sequences in 20 hr and achieved a very good agreement with mapping results from alignment-based methods.

Chromosome Mapping↗