Biomedical subjects

Jin-An Feng

Publications and source records attributed to Jin-An Feng.

5 recordsLinked to original sources

PubMed2006

RepairNET: a bioinformatics toolbox for functional exploration of DNA damage response.

DNA damage response is one of the essential cellular mechanisms to maintaining the genomic integrity of the cell. Aberrations in the mechanism of DNA damage response often result in cancer. We describe here RepairNET, a protein-protein interaction network associated with the DNA damage response. RepairNET is assembled from the published literature by using a protocol that involved computational data mining of the MEDLINE and manual curation. This network represents the current knowledge on the intrinsic signaling pathways related to the DNA damage response process. RepairNET currently contains more than 1,200 proteins with over 2,300 functional interactions. A number of web-interface tools have been implemented to facilitate a user-friendly environment. The users can navigate through the cellular network associated with the DNA damage response via a Java-based interactive graphical interface. In order to help users explore the functional relationships between the interacting proteins, we have assigned functional domains to the proteins in RepairNET based on their sequences. A total of 365 unique functional domains are assigned. RepairNET is available online at http://guanyin.chem.temple.edu/RepairNET.html. It could become an essential resource center for cancer research, providing clues to understanding the functional relationship between proteins in the network, and to building scientific models for the mechanism of DNA damage response and cancer proliferation.

Adaptor Proteins, Signal Transducing↗

PubMed2005

NdPASA: a pairwise sequence alignment server for distantly related proteins.

SUMMARY: NdPASA is a web server specifically designed to optimize sequence alignment between distantly related proteins. The program integrates structure information of the template sequence into a global alignment algorithm by employing neighbor-dependent propensities of amino acids as a unique parameter for alignment. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. NdPASA is most effective in aligning homologous proteins sharing low percentage of sequence identity. The server is designed to aid homologous protein structure modeling. A PSI-BLAST search engine was implemented to help users identify template candidates that are most appropriate for modeling the query sequences.

Algorithms↗

PubMed2005

NdPASA: a novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities.

Sequence alignment has become one of the essential bioinformatics tools in biomedical research. Existing sequence alignment methods can produce reliable alignments for homologous proteins sharing a high percentage of sequence identity. The performance of these methods deteriorates sharply for the sequence pairs sharing less than 25% sequence identity. We report here a new method, NdPASA, for pairwise sequence alignment. This method employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. The values of neighbor-dependent propensity measure the preference of an amino acid pair adopting a particular secondary structure conformation. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Using superpositions of homologous proteins derived from the PSI-BLAST analysis and the Structural Classification of Proteins (SCOP) classification of a nonredundant Protein Data Bank (PDB) database as a gold standard, we show that NdPASA has improved pairwise alignment. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity. For sequence pairs sharing 13-21% sequence identity, NdPASA improves the accuracy of alignment over the conventional global alignment (GA) algorithm using the BLOSUM62 by an average of 8.6%. NdPASA is most effective for aligning query sequences with template sequences whose structure is known. NdPASA can be accessed online at http://astro.temple.edu/feng/Servers/BioinformaticServers.htm.

Algorithms↗

PubMed2004

Repair-FunMap: a functional database of proteins of the DNA repair systems.

UNLABELLED: Repair-FunMap is a functional database of the DNA repair systems. This database contains not only the proteins directly involved in DNA repair, but also the proteins that interact with the DNA repair proteins. A protein interaction network associated with the human DNA repair processes was established according to the functional relationship between proteins in the database. This network represents the current knowledge on the intrinsic signaling pathways related to DNA repair. The Repair-FunMap could become an essential resource center for cancer research, providing clues to understanding the inter-relationship between proteins in the network, and to building scientific models of the DNA repair processes. AVAILABILITY: http://astro.temple.edu/~feng/Servers/BioinformaticServers.htm

Abstracting and Indexing↗

PubMed2003

Exploring the sequence patterns in the alpha-helices of proteins.

This paper reports an extensive sequence analysis of the alpha-helices of proteins. alpha-Helices were extracted from the Protein Data Bank (PDB) and were divided into groups according to their sizes. It was found that some amino acids had differential propensity values for adopting helical conformation in short, medium and long alpha-helices. Pro and Trp had a significantly higher propensity for helical conformation in short helices than in medium and long helices. Trp was the strongest helix conformer in short helices. Sequence patterns favoring helical conformation were derived from a neighbor-dependent sequence analysis of proteins, which calculated the effect of neighboring amino acid type on the propensity of residues for adopting a particular secondary structure in proteins. This method produced an enhanced statistical significance scale that allowed us to explore the positional preference of amino acids for alpha-helical conformations. It was shown that the amino acid pair preference for alpha-helix had a unique pattern and this pattern was not always predictable by assuming proportional contributions from the individual propensity values of the amino acids. Our analysis also yielded a series of amino acid dyads that showed preference for alpha-helix conformation. The data presented in this study, along with our previous study on loop sequences of proteins, should prove useful for developing potential 'codes' for recognizing sequence patterns that are favorable for specific secondary structural elements in proteins.

Computational Biology↗