David H. Mathews, M.D., Ph.D.

David H. Mathews, M.D., Ph.D.

Contact Information

University of Rochester Medical Center
School of Medicine and Dentistry
601 Elmwood Ave, Box 712
Rochester, NY 14642

Fax: (585) 275-6007
Office: (585) 275-1734

Research Bio

Our understanding of the role of RNA in cellular processes has expanded enormously over the last two decades. Originally, RNA was understood to participate in protein expression as a carrier of genetic information (mRNA) and as an adapter molecule (tRNA) for reading the code. Then RNA was discovered to catalyze reactions, including self-splicing, phosphodiester bond cleavage, and peptide bond formation. RNA is now known to play functions in diverse cellular processes, such as development, immunity, RNA editing and modification, and post-transcriptional gene regulation. RNA is also an important player in many diseases, including Prader-Willi, b-thalassemia, and myotonic dystrophy. RNA sequences can be evolved in vitro to catalyze many reactions that are not part of the natural repertoire. Antisense and RNAi can be used to modulate gene expression.



Research in the Mathews lab spans the fields of Computational Biology and Bioinformatics. We are interested in predicting RNA structure and we develop computational tools for targeting RNA with pharmaceuticals and for using RNA as a pharmaceutical (Mathews et al., 1999a).

In collaboration with Doug Turner (University of Rochester) and Michael Zuker (RPI), we have developed software that predicts secondary structure, i.e. the canonical base pairs (Mathews et al., 2004; Mathews et al., 1999b). On average, 73% of base pairs are correctly predicted in a set of diverse sequences with known structures. This accuracy can be improved by constraining the structure prediction using data derived from experiments.

We have also developed software that uses a partition function to predict base pairing probabilities (Mathews, 2004). Using this algorithm, secondary structures can be color annotated according to pairing probability to graphically demonstrate both high probability pairs and low probability pairs that are, on average, not as accurate.

Finally, we are developing methods to predict a secondary structure common to multiple sequences (Mathews & Turner, 2002). The accuracy of structure predictions is dramatically improved by using the information contained in multiple sequences. For example, for a set of poorly predicted 5S rRNA sequences, the average accuracy of base pair prediction improves from 47.8% to 86.4% when the structure common to two sequences is determined.

Recent Journal Articles

Showing the 5 most recent journal articles. 73 available »

2015 Sep 3
"Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data." Nucleic acids research. 2015 Sep 3; 43(15):7247-59. Epub 2015 Jul 13.
2015 Jul 7
Liberman JA, Suddala KC, Aytenfisu A, Chan D, Belashov IA, Salim M, Mathews DH, Spitale RC, Walter NG, Wedekind JE. "Structural analysis of a class III preQ1 riboswitch reveals an aptamer distant from a ribosome-binding site regulated by fast dynamics." Proceedings of the National Academy of Sciences of the United States of America. 2015 Jul 7; 112(27):E3485-94. Epub 2015 Jun 23.
2015
Sloma MF, Mathews DH. "Improving RNA secondary structure prediction with structure mapping data." Methods in enzymology. 2015 553:91-114. Epub 2015 Feb 03.
2015
Fu Y, Xu ZZ, Lu ZJ, Zhao S, Mathews DH. "Discovery of Novel ncRNA Sequences in Multiple Genome Alignments on the Basis of Conserved and Stable Secondary Structures." PloS one. 2015 10(6):e0130200. Epub 2015 Jun 15.
2014 Aug 1
Guy MP, Young DL, Payea MJ, Zhang X, Kon Y, Dean KM, Grayhack EJ, Mathews DH, Fields S, Phizicky EM. "Identification of the determinants of tRNA function and susceptibility to rapid tRNA decay by high-throughput in vivo analysis." Genes & development. 2014 Aug 1; 28(15):1721-32.

Current Appointments

Associate Professor - Department of Biochemistry and Biophysics (SMD) - Primary
Associate Professor - Department of Biostatistics and Computational Biology (SMD)

Education

MD | Medicine | Univ Rochester Sch Med/Dent2003
PhD | Chemistry | University of Rochester2002
BS | Physics | University of Rochester1994