Protein interaction network for Alzheimer's disease using computational approach

Alzheimer''s disease (AD) is the most common form of dementia. It is the sixth leading cause of death in old age people. Despite recent advances in the field of drug design, the medical treatment for the disease is purely symptomatic and hardly effective. Thus there is a need to understand the molecular mechanism behind the disease in order to improve the drug aspects of the disease. We provided two contributions in the field of proteomics in drug design. First, we have constructed a protein-protein interaction network for Alzheimer''s disease reviewed proteins with 1412 interactions predicted among 969 proteins. Second, the disease proteins were given confidence scores to prioritize and then analyzed for their homology nature with respect to paralogs and homologs. The homology persisted with the mouse giving a basis for drug design phase. The method will create a new drug design technique in the field of bioinformatics by linking drug design process with protein-protein interactions via signal pathways. This method can be improvised for other diseases in future.     

Linkage relationships of biochemical markers to Q- and C-band variants in a large black kindred

Summary Lod scores are reported for 86 biochemical to cytogenetic marker comparisons in a Black kindred. Analysis with unconfirmed locus assignments resulted in 12 exclusions of close linkage.This paper is based on a thesis submitted by the senior author in partial fulfillment of the Ph.D. degree at North Carolina State University, Raleigh.Research supported by the National Heart and Lung Institute Grant HLO-3341, National Institute of Mental Health Grant MH 26621, and National Institute of General Medical Sciences Grant GN 16697; paper number 6281 of the Journal Series of the North Carolina Agricultural Research Service, Raleigh, North Carolina.     

Gametic equilibrium between 24 polymorphic markers

Summary Pairs of unlinked genetic markers (blood cell antigens and enzymes and serum proteins) were tested for gametic equilibrium (GE) in data from 508 unrelated individuals from different regions of North America. A total of 24 markers were considered in the study. Only 14 of 262 pairs (5.3%) of markers deviated from GE at the 5% significance level and only 6 pairs (2.3%) remained in significant disequilibrium after accounting for genetic heterogeneity among regional groups. The particular combinations of alleles or one-locus genotypes that showed significant association were identified in case they might be replicated in future studies. On the basis of this study alone, however, there is no reason to suspect disequilibrium between the pairs of markers studied.     

Negative feedback enhances robustness in the yeast polarity establishment circuit

Many cells undergo symmetry-breaking polarization toward a randomly oriented "front" in the absence of spatial cues. In budding yeast, such polarization involves a positive feedback loop that enables amplification of stochastically arising clusters of polarity factors. Previous mathematical modeling suggested that, if more than one cluster were amplified, the clusters would compete for limiting resources and the largest would "win," explaining why yeast cells always make one and only one bud. Here, using imaging with improved spatiotemporal resolution, we show the transient coexistence of multiple clusters during polarity establishment, as predicted by the model. Unexpectedly, we also find that initial polarity factor clustering is oscillatory, revealing the presence of a negative feedback loop that disperses the factors. Mathematical modeling predicts that negative feedback would confer robustness to the polarity circuit and make the kinetics of competition between polarity factor clusters relatively insensitive to polarity factor concentration. These predictions are confirmed experimentally.