Introduction:
Bioinformatics is an interdisciplinary field that utilizes the involvement of computers for storing, collecting, organizing, analyzing, manipulating, presenting, and sharing the biological data. Bioinformatics and computational biology are the terms that are often used synonymously. According to US National Institutes of Health (NIH) Bioinformatics is defined as Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.
Whereas Computational Biology is defined as: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. The term Bioinformatik” in Germany is used for both, whereas the term “Computerbiologie” is not in demand. Due to technological advancements like high-throughput sequencing methods, DNA and protein microarrays, mass-spectrometry data and supercomputers have helped to transform molecular biological data into high throughput data. To handle this extensive data, bioinformatician is required who can manage and understand the data generated. They design the algorithms on how the data can be efficiently processed and stored. They not only need to be capable of developing or adapting algorithms and their implementation but also need to be able to communicate with the other involved scientists from various fields. Bioinformatician develops simulations to test theoretical models of biological or chemical processes, possibly derived from data analysis. Verified models can be implemented in predictive programs that will, e.g., allow narrowing down the number of critical biological experiments in drug research (known as rational drug design). The field works in collaboration with computational biology that focuses on designing and operating the biological databases. Bioinformatician works on the platform for interpretation and analysis of biological data. Bioinformatics is emerging as an essential tool for the management of modern biological data in the field of biology and medicine. The main tools for a bioinformatician are designed algorithm; computer software programs and the high-speed internet. The routinely used bioinformatics tools include software programs such as BLAST (Basic Local Alignment Search tool), Clustal W (Multiple sequence alignment); NGS (Next Generation analysis tools); Drug Discovery tools that are both open source and downloadable. With the advent of the human genome project analyzing the genome sequence data, is one of the critical achievements of bioinformatics to date. The significant prospects of bioinformatics involve its potential involvement in understanding the function of the human genome, significant for identifying drug targets and individualized drug therapy. The primary goals of bioinformatician are:
1. Database Curation; Database Integrity and Interoperability
2. Consistency; Error prevention and Correction,
3. Data derivation and Ontology
4. Privacy maintenance and Data mining
One of the most fundamental activities for bioinformatician is the analysis of the sequence of DNA and proteins utilizing commercially available algorithms and databases. The research group involves clinicians to molecular biologists to discover the composition of large and complex biological molecules. The study group also focuses on how to use sophisticated software programs for retrieving, sorting out, analyzing, predicting, and storing DNA and protein sequence data.
The different file formats used for storing DNA and protein sequence are :
Fasta- A short summarized format widely used by onsite in silico tools.
Genbank – It is the standard sequence file format, used by NCBI. It provides the information about the sequence along with its sequence characters.
EMBL – The EMBL format is similar to the Genbank format that is utilized by EMBL laboratory.
ABI - It is the format used for storing Sanger sequencing in the form of binary data. The format is widely used to visualize the trace data and analyze the

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