Area of Research
Dr. Daisuke Kihara
Principal Investigator
Our research interests lie in the area of bioinformatics. We employ computational methods to elucidate intertwined relationships between protein/gene sequences, structure, function, interactions, genome, and pathways. The ultimate goal of our research projects is to obtain new, comprehensive understanding of how structures and functions are coded in molecular sequences and how functions of molecules are orchestrated in a cell.
Specifically, we develop and apply novel computational methods for...
- Predicting protein structure from sequence
- Predicting protein function from sequence and structure
- Predicting protein-protein and protein-ligand interactions
- Predicting functional sites in sequences
- Genome-scale function and structure annotation
- Analyzing functional units in networks
More information can be found on our research projects page here.
Research Highlights
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ESG is our new sequence similarity-based protein function prediction server. In essence, it further applies PFP iteratively and obtains superior performance in terms of prediction accuracy. Visit the server to submit a sequence or read the paper in Bioinformatics. ESG annotates query sequences with Gene Ontology terms by assigning probability to each annotation. Statistical framework of ESG improves the prediction accuracy by iteratively taking into account the neighborhood of query protein in the similarity based sequence space. |
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PFP is our sequence similarity-based protein function prediction server designed to predict GO annotations for a query protein sequence beyond what can be found by searching conventional databases. Visit the server to submit a sequence or read the paper on Protein Science. PFP has achieved the highest total score among participating servers in a function prediciton contest held at AFP-SIG'05, ISMB 2005, and also was the best method in the head-to-head perfomance comparison in the function prediciton category at CASP7. |
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3D-Surfer is web-based software for protein surface comparison and analysis. The server integrates repertoire of methods to assist in high throughput screening and visualization of protein surface comparisons. The surface representation enables a very fast structure search; It takes a couple of seconds to perform an exhaustive comparison between a single protein surface to all protein structures in the current PDB (over 80,000 chains). Visit the server or read the paper on Proteins. |
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Sub-AQUA predicts quality of protein 3D structure models by combining a score for assessing the target-template alignment stability and the residue environment. The RMSD value or GDT-TS score of the model to the native structure will be predicted. Check the paper! |
Recent News
- New members in our lab:Shuai Liu, Yidi Wang, Wei-Chia SUn, Min-Su Kong. All welcome!
- Luciano and Muyi will rotate with our lab from Biology and PULSe. Welcome!
- "Effect of using suboptimal alignments in template-based protein structure prediction" by H. Chen & D. Kihara, accepted for Proteins.
- "Molecular surface representation using 3D Zernike descriptors for protein shape comparison and docking" by D. Kihara, L. Sael, R. Chikhi, & J. Esquivel-Rodriguez accepted for Curr. Protein and Peptide Science.
- Lee Sael & Daisuke Kihara, "Protein surface representation for application to comparing low-resolution protein structure data" by L. Sael & D. Kihara accepted for BMC Bioinformatics (GIW 2010 issue).
- We welcome Mingjie Tang in our lab. Welcome, Mingjie.
- Sael finished her PhD thesis defence. Congratulations, Dr. Lee!
- Our group has moved to Hockmyer Structural Biology building. Rooms are 229 (Kihara), 237, 238 and 161A.
News Archives are available here.
Openings
Kihara Bioinformatics Laboratory is always looking for new people to join the lab. Our current list of openings is available here.