BIOINFORMATICS PROGRAM St. Edward’s University Genomics Education Partnership (GEP) Genomics Consortium for Active Teaching (GCAT)
Curriculum Genomics Track (11-12hrs): Evolution Biochemistry I, II Cell, Micro, Neuro Genomics Track (11-12hrs): Evolution Biochemistry I, II Cell, Micro, Neuro Bio-Math Track Track (11-12hrs): Linear Algebra Differential Equation Prob/Theory Stats. Cell, Micro, Neuro Bio-Math Track Track (11-12hrs): Linear Algebra Differential Equation Prob/Theory Stats. Cell, Micro, Neuro Cells/Org. Sys. Organisms/Pop Gen. Chem Analytic Chem Calculus I Calculus II Intro BINF Y1 Molecular Organic I Java I Calculus III Discrete Java II Genomics Perl, Python, R Y2 Applied Stats Alg. & Data Struct. Alg. & Data Struct. Senior Seminar Research (3x) Bioinformatics Y3,4
Biological Programming Data structures: scalars, arrays, hashes Control Structures Blast: principles, parsing (BioPerl) Distance matrices: dissimilarity (Jaccard) Phylogenetic Profiles Protein conservation/annotation Phylogenetic Profiles
Bioinformatics Construct simple hidden Markov model Membrane Proteins: LILWLVIAVVLMSVFQSFGP PSLLASIFISWFPMLLLIGVWIFFM YFVIQTYLPCIMTVILSQVSFW Soluble Proteins: MAKN RQMQGGGGKGAMSFGKSKARMLTEDQI KTTFADVAGCDEAKEEVAELVEYLREPS RFQKLGGKIPKGVLMVGPPGTGKTLLAK AIAGEAKVPF State Sequences: >FTSH_ECOLI iiiiMMMMMMMMMMMMMMMMMMMMoooooooooooooooooooooooooooooo ooo oooooooooooooooooooooooooooooooooooMMMMMMMMMMMMMMMMMM MMM Iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii Other Projects: Smith-Waterman Multivariate Analysis (PCoA) RNASeq Analysis (Tophat/Bowtie)
Senior Research Projects
No Burn Light Burn High Burn Unweighted (rare species) Isolate DNA PCR 454 Sequencing Primer Sets 454 Sequencing Primer Sets Soil samples QIIME Sequence Filtering depleted of barcodes/ primers < 200 removed Ave. quality score <25 Ambiguous base calls Homopolymer runs (>6x) Chimeras depleted of barcodes/ primers < 200 removed Ave. quality score <25 Ambiguous base calls Homopolymer runs (>6x) Chimeras OTU Identification Clustering at 3% divergence (97% similarity) Clustering at 3% divergence (97% similarity) OTU Classification Sequences were aligned to the Silva database using the PyNAST algorithm (minimum percent identity was set at 80%)