Protein Inference Engine (PIE): protein post-translational modifications from top-down and bottom-up data
Jefferys, S., and Giddings, M.C., Baking a mass-spectrometry data PIE with McMC and simulated annealing: predicting protein post-translational modifications from integrated top-down and bottom-up data. Bioinformatics (2011) 27 (6): 844-852. Abstract.
GFS: A software system for identifying proteins by comparison of MS and MS/MS data to unannotated genome sequence.
Wisz, M.S., Khatun, J., and Giddings, M.C. Computational methods enabling genome-based protein identification from large, complex genomes using mass spectrometry data. in Third IEEE Workshop on Genomic Signal Processing and Statistics (GENSIPS). 2005. Newport, RI. PDF
Wisz, M.S., Suarez, M.K., Holmes, M.R., and Giddings, M.C., GFSWeb: a web tool for genome-based identification of proteins from mass spectrometric samples. J Proteome Res, 2004. 3(6): p. 1292-5. Summary.
Giddings, M.C., Shah, A.A., Gesteland, R.F., and Moore, M.B. (2003). “Genome-based peptide fingerprint scanning.” Proc. Nat. Acad. Sci. USA. 100(1):20-25. Abstract.
PROCLAME: Protein Cleavage and Modification Engine.
Holmes, M.R. and Giddings, M.C., Prediction of posttranslational modifications using intact-protein mass spectrometric data. Anal Chem, 2004. 76(2): p. 276-82. PubMed Abstract.
BaseFinder: a flexible software for the analysis of trace data from fluorescence-based sequencers.
Giddings, M.C., Severin, J., Westphall, M., Wu, J., and Smith, L.M. 1998. A software system for data analysis in automated DNA sequencing, Genome Research, 8(6):644-665. Abstract.
Giddings, M.C., Brumley, R.L., Haker, M., and Smith, L.M. 1993. An adaptive, object-oriented strategy for base calling in DNA sequence analysis. Nucleic Acids Res. 21(19), 4530-4540. Abstract.
Recode: A database of recoding events.
Baranov, P.V., Gurvich, O.L., Fayet, O., Prere, M.F., Miller, W.A., Gesteland, R.F., Atkins, J.F., and Giddings M.C. 2001 Recode: A Database of Frameshifting, Bypassing and Codon Redefinition utilized for gene expression. Nucleic Acids Research, 29(1):264-267 Abstract.
Antisense oligo efficacy predictions by neural networks, and a database of antisense oligos.
Giddings, M., Matveeva, O., Atkins, J., and Gesteland, R. 2000. ODNBase – A web database for antisense oligonucleotide effectiveness studies. Bioinformatics, 16(9):843-844. Abstract.
Giddings, M.C., Shah, A.A., Freier, S., Atkins, J.F., Gesteland, R.F. and Matveeva, O.V. 2002. Artificial neural network prediction of antisense oligodeoxynucleotide activity. Nucleic Acids Res., 30(19), 4295-304 Abstract
freqAnalysis: frameshift prediction using heptamer statistics.
Shah, A.A., Giddings, M.C., Parvaz, J.B., Gesteland, R.F., Atkins, J.F., and Ivanov, I.P., Computational identification of putative programmed translational frameshift sites. Bioinformatics, 2002. 18(8): 1046-53. Abstract.
Antibiotic Resistance
Su, H.c., Ramkisson, K., Doolittle, J., Clark, M., Khatun, J., Secrest, A., Wolfgang, M.C., and Giddings, M.C., The development of ciprofloxacin resistance in Pseudomonas aeruginosa involves multiple response stages and multiple proteins. Antimicrob. Agents Chemother, 2010. doi:10.1128/AAC.00762-10. Abstract.
Ultra-Structure
Maier, C., Long, J.g., Hemminger, B.M., Giddings, M.C., Ultra-Structure database design methodology for managing systems biology data and analyses. BMC Bioinformatics 2009, 10:254. Full Text.
Other
Holmes, M.R., Ramkissoon, K., and Giddings, M.C., Proteomics and Protein Identification, in “Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Third Edition”, Edited by Andreas D. Baxevanis and B. F. Francis Ouellette, 2005. Hoboken, NJ: John Wiley & Sons. ISBN: 0-471-47878-4. Link to purchase book.
Khatun, J., Ramkissoon, K., and Giddings, M.C., Fragmentation Characteristics of Collision-Induced Dissociation in MALDI TOF/TOF Mass Spectrometry. Anal. Chem., 2007, 79 (8), pp 3032–3040. Abstract.