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The following topics are dealt with: computations in bioinformatics and bioscience; data, signal, and image processing; high performance computing technology and application; distributed systems and data distributions; service computing and grid computing; computer graphics, vision, and visualization; networks and network security; optimization and artificial intelligent and neural networks; Internet...
In accordance with the increasing amount of information concerning individual differences in drug response and molecular interaction, the role of in silico prediction of drug interaction on a pathway level is becoming more and more important. However, in view of the interferences for the identification of new drug interactions, most conventional information models of a biological pathway would have...
DNA-binding proteins are of utmost importance to gene regulation. The identification of DNA-binding domains is useful for understanding the regulation mechanisms of DNA-binding proteins. In this study, we proposed a method to determine whether a domain or a protein can has DNA binding capability by considering evolutionary conservation of DNA-binding residues. Our method achieves high precision and...
This paper describes MLIP, a multiprocessor two- point genetic linkage analysis system that supports statistical calculations, such as the posterior probability of linkage (PPL), based on the full multidimensional parameter space implicit in the linkage likelihood. We provide empirical results on a wide variety of data showing that MLIP does significantly speed up two-point log-likelihood ratio calculations...
Numerous genome projects have produced a large and ever increasing amount of genomic sequence data. However, the biological functions of many proteins encoded by the sequences remain unknown. Protein function annotation and prediction become an essential and challenging task of post-genomic research. In this paper, we present an automated protein function prediction system based on a set of proteins...
The purpose of the proposed study was to provide a solution to the Wisconsin diagnostic breast cancer (WDBC) classification problem. The WDBC dataset, provided by the University of Wisconsin Hospital, was derived from a group of images using fine needle aspiration (biopsies) of the breast. An ensemble of support vector machines (SVM's) was employed in this study. Support vectors with linear, polynomial...
Protein structural class is the most basic and important classification of protein structures. The prediction technique of protein structural class has been developing for decades. Two popular methods, the amino acid frequency based methods and amino acid arrangement and long-term correlation based methods, were proposed in previous work. However, there are opposite advantages and disadvantages in...
The goal of this work is to find optimal numerical solvers to study models of biological systems of interest. We report 2 simple rules to select the optimal numerical solver(s) for solving stiff, complex oscillatory systems. Numerical solvers currently used to solve mathematical models in systems biology can be ill-conditioned due to stiffness. As a case study, we choose the classic Belousov-Zhabotinskii...
Detecting overlapping genes from multiple gene lists is a frequently used procedure in microarray- based studies. However in previous studies, the intersection operations of gene lists, formally known as the Intersection-Union Tests (IUTs), were performed without being aware of the incurred changes in Type 1 error rate. We presented an IUT adjustment procedure, called Relaxed IUT (RIUT), which is...
Inference of evolutionary trees using the maximum likelihood principle is NP-hard. Therefore, all practical methods rely on heuristics. The topological transformations often used in heuristics are nearest neighbor interchange (NNI), sub-tree prune and regraft (SPR) and tree bisection and reconnection (TBR). However, these topological transformations often fall easily into local optima, since there...
The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It is sensitive to initial partitions, its result is prone to the local minima, and it is only applicable to data with spherical-shape clusters. The last shortcoming means that we must assume that gene expression data at the different...
Recent outbreaks of highly pathogenic avian influenza A virus infections in poultry and humans have caused considerable concerns about a future influenza pandemic in humans. In order to prepare such an unavoidable pandemic incident, effective methods for detecting and identifying dangerous virus strains that are lethal to human life must be developed. For this purpose, we developed a Web tool called...
Gene pathway can be defined as a group of genes that interact with each other to perform some biological processes. Along with the efforts to identify the individual genes that play vital roles in a particular disease, there is a growing interest in identifying the roles of gene pathways in such diseases. This paper proposes an innovative method which measures the significance of the gene pathways...
A survey of microarray repositories reveals that their contents and data models are heterogeneous, and that repositories developed for different communities have become "silo-ed" over time. A community maintained resource, ArrayWiki, resolves these problems by uniting disparate meta-data that are difficult for users to find. This resource provides users with simple text-based searches across...
We introduce BioGraphE, a general, scaleable integration platform for connecting graph problems in biology to computational solvers and high-performance systems. This framework will enable computational scientists to identify and bring in graph analysis applications and to easily connect them to efficient and powerful computational software and hardware that are specifically designed and tuned to...
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