Texas A&M University
Degree: Doctor of Philosophy in Biology
University of Texas at El Paso
Degree: Master of Science in Chemistry
Massachusetts Institute of Technology
Degree: Bachelor of Science in Physics
Research InterestsHave broad background in computational biology of RNA structural features and sequence pattern detection of genetic signatures. Expertise using smart and connected technologies from prior NSF and NIH grants. Carried out research and molecular structure analysis on numerous model organisms using machine learning techniques and large databases. Expanded research to include biomedical informatics and next-generation sequencing analysis. As co-director of Biomedical Informatics Unit (BIU) at MSM, responsible for high performance computing and secure storage of patient health information (PHI) using a High Performance Cluster (HPC) with 168 cores and 120 Tb of attached storage to support genomic and Big Data biomedical studies.
Digby, D., and Seffens, W., (2005), Step-Wise Mutations of mRNA Sequences Lead to Progressive Changes in Calculated
Folding Free Energies, Advances in Bioinformatics and its Applications, World Scientific
Publishing Co. Series in Mathematical Biology and Medicine, Vol. 8. p. 341-350.
David Digby, Fisseha Abebe and William Seffens (2002), Runs of Amino Acids are Longer Than Expected in Proteins Based on a Graph Theory Representation of the Genetic Code, J. Biological Systems 10(4):319-335.
Seffens, W. and Digby, D., (2000), Gene Sequences are Locally Optimized for Global mRNA Folding, Optimization in Computational Chemistry and Molecular Biology, ( C. Floudas and P. Pardalos, eds.) Kluwer Academic Press. p. 131-140.
Seffens, W. and Digby, D., (1999), mRNAs Have Greater Calculated Folding Free Energies Than Shuffled or Codon Choice Randomized Sequences, Nucleic Acids Research 27: 1578-1584.