Current trends in Bioinformatics: An Insight (original) (raw)

Review on Applicability of Bioinformatics in Current Research and Database Management

A generation of new science has evolved with the development of bioinformatics and computational biology which have molecular biology as an integrated part. In the past decade, technological advances have promoted a prominent development in expertise and knowledge in the molecular basis of phenotypes. In Bioinformatics, biological data is evaluated by computational science and processed in a more statistical and meaningful way. It includes the collection classification storage and evaluation of biochemical and organic statistics using computers in particular as implemented in molecular genetics and genomics. Computational Biology and Bioinformatics are emerging branches of science and include the use of techniques and concepts from informatics statistics, mathematics, chemistry, biochemistry, physics, and linguistics. Therefore, bioinformatics and computational biology have sought to triumph over many challenges of which a few are listed in this overview. This evaluation intends to provide insight into numerous bioinformatics databases and their uses in the analysis of biological records exploring approaches emerging methodologies strategies tools that can provide scientific meaning to the information generated.

A Summary of Genomic Databases: Overview and Discussion

Studies in Computational Intelligence, 2009

In the last few years both the amount of electronically stored biological data and the number of biological data repositories grew up significantly (today, more than eight hundred can be counted thereof). In spite of the enormous amount of available resources, a user may be disoriented when he/she searches for specific data. Thus, the accurate analysis of biological data and repositories turn out to be useful to obtain a systematic view of biological database structures, tools and contents and, eventually, to facilitate the access and recovery of such data. In this chapter, we propose an analysis of genomic databases, which are databases of fundamental importance for the research in bioinformatics. In particular, we provide a small catalog of 74 selected genomic databases, analyzed and classified by considering both their biological contents and their technical features (e.g, how they may be queried, the database schemas they are based on, the different data formats, etc.). We think that such a work may be an useful guide and reference for everyone needing to access and to retrieve information from genomic databases.

BIOINFORMATICSAPPLICATIONS NOTE

2000

Summary: The Linnaeus Centre for Bioinformatics Data Warehouse (LCB-DWH) is a web-based infrastructure for reliable and secure microarray gene expression data management and analysis that pro- vides an online service for the scientific community. The LCB-DWH is an effort towards a complete system for storage (using the BASE sys- tem),analysis andpublicationof microarraydata.Importantfeaturesof the system include: access to established methods within

Scientific databases Biological data management " Principles of Modern Database Systems "

1. Biological data is highly complex when compared with most other domains or applications. Definitions of such data must thus be able to represent a complex substructure of data as well as relationships and to ensure that information is not lost during biological data modeling. Biological information systems must be able to represent any level of complexity in any data schema, relationship, or schema substructure. A good example of such system is MITOMAP database documenting the human mitochondrial genome (http://www.mitomap.org). The database information include data and their relationship about ca. 17,000 nucleotide bases of the mitochondrial DNA; 52 gene loci encoding mRNAs, rRNAs and tRNAs; over 1,500 known population variants and over 60 disease associations. MITOMAP includes links to over 3,000 literature references.

Bioinformatics: Application of Information Technology in Biological Science

Bioinformatics was applied in the creation and maintenance of a database to store biological information at the beginning of the "genomic revolution", such as nucleotide and amino acid sequences. Development of this type of database involved not only design issues but the development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data. Bioinformatics and computational biology are frequently integrated with experimental studies as well, with bioinformatics emphasizing informatics and statistics, while computational biology emphasizes development of theoretical methods, mathematical modeling, and computational simulation techniques to find solution for genetic problems. Bioinformatics studies include analysis and integration of genomics data, prediction of protein function from sequence, and comparisons of protein ligands to identify target effects of drugs. Computational biology includes simulation of protein motion and folding and how proteins interact with each other.

Recent Trends and Developments in Bioinformatics: Challenges and Opportunities

Use of bioinformatics tools in life sciences have become necessary to analyze experimental data since omics have emerged in this field. The large amount of data is a challenge for the biological community as most biologists are not familiar to informatics and statistical interpretation and concepts. An interdisciplinary collaboration is welcome to explain to data analysts the needs of biologists, and to help biologists to understand their data. Here, we provide an opportunistic view of bioinformatics and its growth for various disciplines. Hundreds of tools, pipelines and applications have been developed to analyze this ample amount of biological data being generated on a daily basis at the global level. Galaxy is one such platform created in 2005 to allow scientists to analyze their data and share workflows in a reproducible, transparent, and accessible way to generate biologically meaningful information. With the consequential steps from NIH, EBI and other reputed institutions, several global initiatives have been proposed and implemented. One such initiative in Africa is H3ABionet, which is focusing on the development of Bioinformatics all over Africa and to connect African countries to the rest of the world technically.

Role of Computers in Bioinformatics by Using Different Biological Datasets

IOSR Journal of Computer Engineering, 2014

The amount and variety of data in natural sciences increases rapidly. Data abstraction, data manipulation and pattern discovery techniques are of great need in order to deal with such large quantities. Integration between different sources of data is also of major interest, as complex relations may arise. Biology is a good example of a field that provides extensive, highly variable and multi-sources data. The scope of these investigations has now expanded greatly owing to the development of high throughout sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. We have developed a new software package, molecular genetics analysis to integrate their diverse data and tools under Common Graphical User Interfaces (GUIs) by using BLAST, FASTA data searches. One of the most exciting things about being involved in computer programming and biology is that both fields are rich in new techniques and results. The illumina is sequence analyzer in Next Generation Sequence Technology.