Sunday, January 12, 2014

A Study on Bioinformatics Algorithms: Introduction


      DNA is a polymer and it can be considered as a macromolecule responsible for Cell automation and Cell replication. It is a blueprint that contains smaller units named as Nucleotides that make up the DNA. The human genetic material consists of 3 billion nucleotides, assembled into 23 sets called chromosomes. These 3 billion nucleotides are stored in the databases called Nucleotide sequence databases.

      1. DDBJ          (DNA Data bank of Japan)
      2. NCBI           (National Center for Biotechnology Information)
      3. EMBL         (European Molecular Biology laboratory)

   The main operation that is performed upon these databases is searching a sequence (using query sequence). The search programs like BLAST and FASTA are used for this purpose.

    How did these programs were designed and implemented? Who did write these programs? As a BioInformatics scientist, can we write these programs? These are the questions that will be analyzed and answered under this topic.

  Moreover we will study what are the different types of BioInformatics algorithms available. The following are the very few type of BioInformatics algorithms.

               Exhaustive Search Algorithms
              Greedy Algorithms
              Dynamic Programming Algorithms
              Divide and Conquer Algorithms
              Graph Algorithms
              Randomized Algorithms
              Combinational pattern matching Algorithms
              Hidden Markov Models and so on

   In the same way we have to solve different types of BioInformatics problems in Bioinformatics. Few of the problems are listed below.

             DNA sequencing
             DNA Mapping
             Predicting Genes
             Comparing Genes
             Genome Rearrangements and so on

   Applying a particular type of algorithm to a Bioinformatics problem is based on the nature of the problem. Exhaustive search algorithms are used for Mapping DNA and finding signals. Greedy algorithms are more suitable for Genome Rearrangements. Divide and Conquer algorithms are solving Comparing Sequence Problems.

    We may wonder that as a biologist why should we learn algorithms, which are intended for computer science. The answer is straightforward. The convergence of Biology and computer science is called as BIOINFORMATICS. To be a real Biologist we have to acquire skills in Biology as well as in computer science. Biological skills include Cell life cycle, double helix structure of DNA, Transcription, and Translation and down the line. In Computer Science, we should learn about how to write efficient computer program for solving BioInformatics problems. In this point I like to remember that one of the man (Crick) who finds the DNA double Helix structure is not a Biologist but he is a physicist.

  Study of BioInformatics algorithms needs more mathematical knowledge than biological skills. By acquiring sufficient skills in Biology, Computer Science and Mathematics, we will become a “True Biologist”.





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