J. K. Wickiser Lab

Network Science

At its most fundamental level, Biology is the control and interplay between a vast number coupled chemical reactions.  These chemical reactions control the basic processes of life as well as providing rapid response mechanisms to counter a plethora of environmental changes.  Network Science involves the study of the relatedness of seemingly disparate phenomena.

Pyramidine metabolic network (KEGG)

Gene expression microarrays

We are using the power of microarray technology to assess the up- and down-regulation of genes at the mRNA level in several different experiments.  The information gained from this analysis helps identify “hot spots” of activity in response to a stimulus such as a chemical contaminant or oxygen starvation conditions.  The significant conclusions are drawn from identifying the relationships between the nodes of these network maps.

Quantitative (Real Time) PCR at USMA

The department has recently acquired an multicolor Q-PCR system (Agilent) in order to observe quantitative changes in gene expression.  We are using this instrument to support the microarray results for individual genes as well as extend the investigation of certain genes.

High Throughput Sequencing capability at USMA

Beckman Coulter GenomeLab apparatus

Beckman Coulter GenomeLab apparatus

An explosion in data from the study of biological circuitry in living organisms is forthcoming due to the genomic revolution.  The advent of efficient, reliable, and affordable high throughput nucleic acids sequencing devices is allowing the determination of organisms’ genomes, as well as the study of gene expression by monitoring the levels of specific messenger RNA transcripts.

A central piece of the department’s modernization effort is the Beckman Coulter GenomeLab apparatus which has ushered in an era of cadet-conducted systems biology study.  Cadets now have the opportunity to design and conduct genomic and gene expression analysis experiments on a wide range of model organisms.


Of course, the tremendous amount of data generated by this type of instrument requires computational expertise to provide meaningful data that will address hypothesis-driven research efforts.  Hence, we intend to develop our Bioinformatics efforts through collaborations and in-house expertise