A Study on Bioinformatics Algorithms: Aim and Objective

           My aim is to study varies Bioinformatics related problems and finding solution with background knowledge of Molecular Biology.  Learning Molecular Biology gives me pleasure and more innovative ideas. Since I am a very small species in this world, I cannot analysis all the problems, which are related to this field. So I choose a particular problem named as Motif Finding Problem, which is closely related to Sequence alignment problem.

      This Motif Finding Problem can be solved my several techniques as listed below.

1.     Exhaustive Search Method.

2.     Randomized Algorithms.

3.     Greedy Algorithms.

            Exhaustive Search Method analysis the complete sequence of billions of input combinations. Even   today’s modern advanced pipelined Microprocessor chip like Pentium IV cannot solve it with reasonable execution time. But analyzing all possible sequence of input is only the true method for finding the solution for Motif Finding problem. Here I will provide programs in C language to solve Motif Finding Problem using Exhaustive Search method.

         Randomized algorithms are based on probability Theory. Randomized algorithms are often used in hard problems like Motif Finding where an exact, Polynomial-time algorithm is not known.

             The Greedy Method tries to solve Motif Finding Problem by taking inputs and producing outputs that should satisfies some constraints. Any output that satisfies these constrains is called a feasible solution. We have to find a feasible solution that either maximizing or minimizing a given objective function. In our case the feasible solution should be maximized. A feasible solution that does this is called an optimal solution.

               Here I am trying to find the best solution for Motif Finding Problem that should lead me to obtain Nobel Price within my lifetime. The techniques like Exhaustive Search, Randomized Algorithms and Greedy methods are only based on single Microprocessor based systems. That implies that the execution of these algorithms is confined in to a centralized single Microprocessor based systems.

                My Aim and objective is to discover a machine model that should have multiple Microprocessors capable of solving our Motif Finding Problems. So we have to think about distributed computing. A distributed system is one that runs on a collection of machines that do not have shared memory, but still seems to be a single computer. This architecture provides as a fantastic solution for our Motif Finding problem that has billions of inputs which has to be processed.

              Nowadays Distributed computing can be implemented using Variety of ways. The three tier architecture models like Remote Method Invocation (RMI) from Sun Micro Systems Common Object Request Broker Architecture (CORBA) from Object Management Group (OMG), and Distributed Component Object Model (DCOM) from Microsoft are very much related to Distributed Computing. In My study I am planning to analysis about the solution pathways that are based on RMI technology.