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Drena Dobbs

  • University Professor Emeritus


  • B.S., University of Georgia, 1977
  • Ph.D., University of Oregon, 1983

More Information

Professor Dobbs received her B.S. in Biology from the University of Georgia in 1977 and her Ph.D. in Molecular Biology from the University of Oregon in 1983. She received an NIH Postdoctoral Fellowship in 1984, and worked with Elizabeth Blackburn at the University of California, Berkeley. Dr. Dobbs joined Iowa State University in 1987. From 1999 through 2001, she served as the first Chair of the Bioinformatics and Computational Biology (BCB) Graduate Program at ISU. In 2015, Dr. Dobbs was named University Professor.

Research Description

Long-term research goals of the Dobbs group are to understand how proteins and nucleic acids achieve their functional three-dimensional structures and to elucidate mechanisms that determine recognition and regulate interactions among proteins, nucleic acids and other molecules in cells. We use both computational and wet-lab experimental approaches to explore the structure and function of important macromolecular complexes, in close collaboration with several groups at Iowa State, University of Minnesota, and Harvard University.

Current areas of focus include: development of novel antiviral therapies against HIV-1 and other lentiviruses; rational design of zinc finger proteins (ZFPs) as tools for genomic modification and gene therapy; prediction of epitopes and nucleic acid binding residues in proteins; and prediction and experimental validation of structural and functional effects of mutations and SNPs in proteins. For details, please visit the Dobbs Lab website.


Mann CM, Muppirala UK, Dobbs D (2016) Computational prediction of RNA-protein interactions. Methods Mol Biol (in press).

Walia RR, EL-Manzalawy Y, Honavar VG, Dobbs D (2016) Sequence-based prediction of RNA binding residues in proteins. Methods Mol Biol  (in press).

EL-Manzalawy Y, Dobbs D Honavar VG  (2016) In silico identification of antibody-protein binding sites. Methods Mol Biol  (in press).

Noon JB, Qi M, Sill DN, Muppirala U, van den Akker SE, Maier TR, Dobbs D, Mitchum MG, Hewezi T,  Baum TJ (2016) A Plasmodium-like virulence effector of the soybean cyst nematode suppresses plant innate immunity. New Phytol. (in press).

Xue LC, Rodrigues JP, Dobbs D, Honavar V, Bonvin AM (2016) Template-based protein-protein docking exploiting pairwise interfacial residue restraints. Brief Bioinform. 2016 Mar 24. pii: bbw027. [Epub ahead of print]

Dobbs D, Brenner SE, Honavar VG, Jernigan RL, Laederach A, Morris, Q (2016) Regulatory RNA. Pac Symp Biocomput. 21:429-32. 

Muppirala U, Lewis BA, Mann CM, Dobbs D (2016) A motif-based method for predicting interfacial residues in both the RNA and protein components of protein-RNA complexes. Pac Symp Biocomput. 21:445-55.

Xue LC, Dobbs D, Bonvin AM, Honavar V (2015) Computational prediction of protein interfaces: A review of data driven methods. FEBS Lett. Nov 30;589(23):3516-26. 

Umunnakwe CN, Loyd H, Cornick K, Chavez JR, Dobbs D, Carpenter S (2014) Computational modeling suggests dimerization of equine infectious anemia virus Rev is required for RNA binding. Retrovirology Dec 23;11:115.

Andorf CM, Kopylov M, Dobbs D, Koch KE, Stroupe ME, Lawrence CJ, Bass HW (2014) G-quadruplex (G4) motifs in the maize (Zea mays L.) genome are enriched at specific locations in thousands of genes coupled to energy status, hypoxia, low sugar, and nutrient deprivation. J Genet Genomics Dec 20;41(12):627-47.

Walia, RR, Xue, LC, Wilkins, K, El-Manzalawy Y, Dobbs D, Honavar, V (2014) RNABindRPlus: A predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins. PLoS ONE 9(5): e97725. 

Xue LC, Jordan RA, El-Manzalawy Y, Dobbs D, Honavar V (2014) DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction. Proteins Feb;82(2):250-67.

Muppirala, UK, Lewis, BA, Dobbs, D (2013) Computational tools for investigating RNA-protein interaction partners. J Comput Sci Syst Biol. 6(4):182-187

Walia RR, Caragea C, Lewis BA, Towfic FG, Terribilini, M, El-Manzalawy, Y, Dobbs D, Honavar V (2012) Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. BMC Bioinformatics 13, 89. 

Jordan RA, El-Manzalawy Y, Dobbs D, Honavar, V (2012) Predicting protein-protein interface residues using local surface structural similarity. BMC Bioinformatics 13, 41. 

Muppirala,UK, Honavar V, Dobbs D (2011) Predicting RNA-protein interactions using only sequence information. BMC Bioinformatics 12, 489. 

Xue, LC, Dobbs, D, Honavar, V (2011) HomPPI: a class of sequence homology based protein-protein interface prediction methods. BMC Bioinformatics 12, 244.

Steczkiewicz K, Zimmermann MT, Kurcinski M, Lewis BA, Dobbs D, Kloczkowski A, Jernigan RL, Kolinski A, Ginalski K. (2011) Human telomerase model shows the role of the TEN domain in advancing the double helix for the next polymerization step. Proc Natl Acad Sci U S A Jun 7;108(23):9443-8.

Sander JD, Dahlborg EJ, Goodwin MJ, Cade L, Zhang F, Cifuentes D, Curtin SJ, Blackburn JS, Thibodeau-Beganny S, Qi Y, Pierick CJ, Hoffman E, Maeder ML, Khayter C, Reyon D, Dobbs D, Langenau DM, Stupar RM, Giraldez AJ, Voytas DF, Peterson RT, Yeh JR, Joung JK. (2011) Selection-free zinc-finger-nuclease engineering by context-dependent assembly (CoDA). Nat Methods Jan; 8(1):67-9.