ஜர்னல் ஆஃப் கம்ப்யூட்டர் சயின்ஸ் & சிஸ்டம்ஸ் பயாலஜி

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in biological information generated by the scientific community. Biological databases are libraries of life sciences information, collected from scientific experiments, published literature, high-throughput experiment technology, and computational analyses. Information contained in biological databases includes gene function, structure, localization, clinical effects of mutations as well as similarities of biological sequences and structures. This article presents information on some popular bioinformatic databases available online, including sequence, phylogenetic, structure and pathway, and microarray databases.

This paper proposed a new method to build the large scale DNA sequences search system based on web search engine technology. We give a very brief introduction for the methods used in search engine first. Then how to build a DNA search system like Google is illustrated in detail. Since there is no local alignment process, this system is able to provide the ms level search services for billions of DNA sequences in a typical server.

In response to the wide spread of influenza H1N1, a number of alerts were issued by World Health Organization (WHO) in the form of Global Alert and Response updates [3]. Even though there is quick response in the form of alerts exists, the absence of suitable resources makes the task of the research organizations more difficult, which says there is an immediate need to provide a viable solution for reducing this gap. This also suggests Pandemic Preparedness under the Rule of International Law. A frame work is introduced to classify and construct a influenza database which is also called Influenza resource database, Data collection was especially done at Genbank, DDBJ and EMBL then Least formalized selections were Normalized and added to original collection for Classification and construction of unique local database. Classification of Influenza A was done with the RNA segmentation approach. Classification of Influenza B and Influenza C need a specific field of the database for classifying it.