Minimotif Miner
Video on MnM. Developing protein-protein interaction theory is important for our understanding of the cell, disease mechanisms, and to facilitate drug design. The theory behind protein-protein interactions is based on first principle theory of molecular interactions and the identification of a rapidly growing number of short peptide motifs (less than 15 amino acids) that can bind to, or be acted upon by protein domains. Other than those interactions mediated through short motifs we have virtually no ability to predict protein-protein interactions.
My lab is continuing annotation of Minimotif Miner, the first bioinformatics tool that is a comprehensive database of short functional motifs currently containing ~300,000 unique motifs (
Balla et al, 2006,
Rajasekaran et al, 2009, Mi et al., 2012). Minimotif Miner can be used by any scientist to generate new hypotheses about the function of any protein and postulate mechanisms by which mutations cause any human disease.
Current projects are aimed at completing this database, enhancing the specificity of motif definitions. Minimotif Miner was built in collaboration with several scientists at the University of Connecticut and its Health Center. See more on minimotif miner at [wikipedia]
PLEASE CITE USE OF MINIMOTIF MINER WITH THESE PAPERS:
Balla S, Thapar V, Verma S, Luong T, Faghri T, Huang C-H, Rajasekaran S, del Campo JJ, Shinn JH, Mohler WA, Maciejewski MW, Gryk MR, Piccirillo B, Schiller SR, and Schiller MR. (2006). Minimotif Miner, a tool for investigating protein function.. Nat. Methods, 3, 175-177. PMID: 16489333
Rajasekaran S, Balla S, Gradie P, Gryk MR, Kadaveru K, Kundeti V, Maciejewski MW, Mi T, Rubino N, Vyas J, Schiller MR. (2009). Minimotif Miner 2nd release: a database and web system for motif search. Nucleic. Acids Res., 37, D185-190. PMID: 18978024, PMCID: PMC2686579
Mi T, Merlin JC, Deverasetty S, Gryk MR, Bill TJ, Brooks AW, Lee LY, Rathnayake V, Ross CA, Sargeant DP, Strong CL, Watts P, Rajasekaran S, Schiller MR (2012). Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences. Nucleic Acids Res., 40 (database issue), D252-260. PMID: 22146221, PMCID: PMC3245078
PLEASE CITE USE OF MINIMOTIF MINER WITH THESE PAPERS:
Balla S, Thapar V, Verma S, Luong T, Faghri T, Huang C-H, Rajasekaran S, del Campo JJ, Shinn JH, Mohler WA, Maciejewski MW, Gryk MR, Piccirillo B, Schiller SR, and Schiller MR. (2006). Minimotif Miner, a tool for investigating protein function.. Nat. Methods, 3, 175-177. PMID: 16489333
Rajasekaran S, Balla S, Gradie P, Gryk MR, Kadaveru K, Kundeti V, Maciejewski MW, Mi T, Rubino N, Vyas J, Schiller MR. (2009). Minimotif Miner 2nd release: a database and web system for motif search. Nucleic. Acids Res., 37, D185-190. PMID: 18978024, PMCID: PMC2686579
Mi T, Merlin JC, Deverasetty S, Gryk MR, Bill TJ, Brooks AW, Lee LY, Rathnayake V, Ross CA, Sargeant DP, Strong CL, Watts P, Rajasekaran S, Schiller MR (2012). Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences. Nucleic Acids Res., 40 (database issue), D252-260. PMID: 22146221, PMCID: PMC3245078




