Abstract A large number of clustering approaches have been proposed for the analysis of gene expression data obtained from microarray experiments. However, the results of the application of standard clustering methods to genes are limited. These limited results are imposed by the existence of a

In addition to maintaining the GenBankÒ nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s Web site. NCBI resources include Entrez,

The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans

DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a “snapshot ” of transcription levels within the cell. A major challenge in computational biology is to uncover, from such measurements, gene/protein interactions and key

due to the lack of a systematic framework that can accommodate noise, variability, and low replication often typical of microarray data. Results: We develop a Bayesian probabilistic framework for microarray data analysis. At the simplest level, we model log-expression values by independent normal

Abstract—Current database systems lack several specific functionalities that are needed by biological databases. bdbms is an extensible prototype database management system for supporting biological data. bdbms extends the current database systems with: (1) Annotation and provenance management, (2

to be known in advance — all are inferred automatically from the data. This problem naturally arises in a variety of practical situations such as range scanning an object from multiple view points, recovery of biological shapes from two-dimensional slices, and interactive surface sketching.

framework rationalize data of computer viruses and could help in the understanding of other spreading phenomena on communication and social networks. PACS numbers: 05.70.Ln, 05.50.+q Typeset using REVT E X 1 Many social, biological, and communication systems can be properly described by complex

The availability of massive amounts of DNA sequence information has begun to revolutionize the practice of biology. As a result, current large-scale sequencing output, while impressive, is not adequate to keep pace with growing demand and, in particular, is far short of what will be required

Motivation: Rapid, automated means of organizing biological data are required if we hope to keep abreast of the flood of data emanating from sequencing, microarray and similar high-throughput analyses. Faced with the need to validate the annotation of thousands of sequences and to generate