Nicole Baumgarth, Ph.D - April 14, 2009
University of California, Davis
Department of Pathology, Microbiology, & Immunology
"Innate Signals Regulate B Cell Responses To Influenza Virus Infection"
Jamil Momand, Ph.D - April 21, 2009
University of California, Los Angeles
Department of Chemstry & Biochemistry
"Redox Control of Protein Activity"
Reactive oxygen species (ROS) consist of hydroxyl radicals, peroxides and superoxide. Reactive nitrogen species (RNS) consist of nitric oxide (NO), peroxynitrite (ONOO-) and nitrogen dioxide (NO2). Mounting evidence accumulated over the past 15 years indicates that ROS and RNS are natural signaling molecules that mediate reversible nanoswitches that can activate and deactivate metabolic pathways. Proteins susceptible to reversible oxidation by these signaling molecules include the tumor suppressor phosphatase/tensin homolog (PTEN), the p53 tumor suppressor and the metabolic enzyme glycerate 3-phosphate dehydrogenase.
At excessive levels, these signaling molecules contribute to diabetes, neurodegenerative disorders, and cancer. Excessive levels result from inflammation and leakage from mitochondria. One substrate of reversible oxidation is the protein cysteine residue. Reaction of cysteine thiols directly or indirectly with ROS or RNS results in the formation of sulfur-containing molecules that include sulfenic acid, intramolecular disulfide, and glutathionylated cysteine. These oxidation reactions are reversible. The scientific community is unable to predict which protein cysteines are susceptible to reversible oxidation. Fast and accurate predictions of reversible cysteine oxidation sites will expand the repertoire of natural protein targets of these signaling molecules. I will present the Cysteine Oxidation Prediction Algorithm (COPA). COPA predicts reversible oxidation sites on proteins with 80% accuracy.
Tatiana Tatarinova, Ph.D - April 28, 2009
Loyola Marymount University
Department of Mathematics
“Genome Annotation: New Algoriths and Eternal Challenges”
The availability of complete or nearly complete genome sequences and a large number of expressed sequence tags provide new insights into the characteristics of gene structures and promoters of newly sequenced genomes. Due to reasonable cost and improved quality of gene expression experiments we have significant public expression data. Combination of sequence and expression data allows for a more accurate identification of regulatory elements. We will discuss methods for functional annotations of genes, identification of transcription start sites, algorithms for assessment of statistical significance for all sequence motifs. We will also talk about relationship between forces of evolution and nucleotide composition.
Literature (open access papers):
- Insights into corn genes derived from large-scale cDNA sequencing. Alexandrov NN, Brover VV, Freidin S, Troukhan ME, Tatarinova TV, Zhang H, Swaller TJ, Lu YP, Bouck J, Flavell RB, Feldmann KA. Plant Mol Biol. 2009 Jan;69(1-2):179-94.
- Genome-Wide Discovery of cis-Elements in Promoter Sequences Using gene Expression. Troukhan M, Tatarinova T, Bouck J, Flavell RB, Alexandrov NN. OMICS. 2009 Feb 20.
- Features of Arabidopsis genes and genome discovered using full-length cDNAs. Alexandrov NN, Troukhan ME, Brover VV, Tatarinova T, Flavell RB, Feldmann KA. Plant Mol Biol. 2006 Jan;60(1):69-85.
Elisa Maldonado, Ph.D - May 05, 2009
University of California, San Diego
Scripps Institution of Oceanography
“Strategies of Invertebrate Larvae for Dealing with Food Limitations In the Ocean”
Caleb Finch, Ph.D - May 12, 2009
University of Southern California
ARCO-Kieschnick Professor of Gerontology
"The Greying of the Brain Begins Early"
Ron Wasserstein, Executive Director - May 19, 2009
The American Statistical Association
"Science Students and Statistical Thinking"
- Powerpoint slides of talk
- Helping Doctors and Patients Make Sense of Health Statistics
- Medicine Residents' Understanding of the Biostatistics and Results in the Medical Literature
Melisa Hendrata, Ph.D - June 02, 2009
University of California, Santa Barbara
"Dynamical System Model for Simulating Myxobacteria Life Cycle"
Myxobacteria (Myxococcus xanthus) is social bacteria whose entire life cycle is pervaded by cell-cell interactions. When starved, myxobacteria stop swarming outward the colony and organize themselves to undergo developmental stages, which culminate in the formation of fruiting body. Elongated, motile cells inside the fruiting body differentiate into round, non-motile, resistant spores. We develop a bioenergetic-based off-lattice model to simulate myxobacteria life cycle, which includes the swarming, the fruiting body and the sporulation stages. We incorporate Dynamic Energy Budget (DEB) into our model, successfully linking the internal dynamics of the individual cell with the dynamics of the population. Our simulation shows that the coupling of DEB and an additional equation modeling the level of C-signal molecule on the cell surface, automates the transition from the swarming to the fruiting body stages and also the transition between the sub-stages of the fruiting body formation, concluding with sporulation.
Download Biology Paper Reference:
Coupling Cell Movement To Multicellular Development In Myxobacteria
Reference on the math modeling part, the preprint is available online: