Bioinformatics and the undergraduate curriculum essay.

Recent advances involving high-throughput techniques for data generation and analysis have made familiarity with basic bioinformatics concepts and programs a necessity in the biological sciences. Undergraduate students increasingly need training in methods related to finding and retrieving information stored in vast databases. The rapid rise of bioinformatics as a new discipline has challenged many colleges and universities to keep current with their curricula, often in the face of static or dwindling resources. On the plus side, many bioinformatics modules and related databases and software programs are free and accessible online, and interdisciplinary partnerships between existing faculty members and their support staff have proved advantageous in such efforts. We present examples of strategies and methods that have been successfully used to incorporate bioinformatics content into undergraduate curricula.

Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria.

Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results.

A DNA Motif Lexicon: cataloguing and annotating sequences.

The rapid proliferation of genomic DNA sequences has created a significant need for software that can both focus on relatively small areas (such as within genes or promoters) and provide wide-zoom views of patterns across entire genomes. We present our DNA Motif Lexicon that enables users to perform genome-wide searches for motifs of interest and create customizable results pages, where results differ in the degree and extent of annotation. Searching for a particular motif is akin to a word search in a natural language; our motif lexicon speaks to this new time when we will increasingly rely upon DNA dictionaries that offer rich types of annotation. Indeed, the concept of "lexomics", introduced in this paper may be appropriate to the types of meta-analyses appropriate to the deciphering of regulatory information. Currently supporting five genomes, our web-based lexicon allows users to look up motifs of interest and build user-defined result pages to include the following: (1) all base pair locations where a motif is found with links to further search the "neighborhoods" near each of these locations; whether each location of the motif is genic (within) a gene, intergenic, or a bridging sequence (overlapping a gene boundary) (2) NCBI hot-links to nearest upstream and downstream genes for each location (3) statistical information about the query (4) whether the motif is a certain type of repeat (5) links for the reverse, complement and reverse-complement of the motif of interest and (6) hot-links to PubMed abstracts which mention the motif of interest. A software framework facilitates the continual development of new annotation modules. The tool is located at: http://genomics.wheatoncollege.edu/cgi-bin/lexicon.exe.