Sequencing by Hybridization of Long Targets

Sequencing by Hybridization (SBH) reconstructs an n-long target DNA sequence from its biochemically determined l-long subsequences. In the standard approach, the length of a uniformly random sequence that can be unambiguously reconstructed is limited to due to repetitive subsequences causing reconstruction degeneracies. We present a modified sequencing method that overcomes this limitation without the need for different types of biochemical assays and is robust to error

An approach to solve job shop scheduling problem

“A biotechnology device manufacturer needs to devise effective scheduling algorithms for its testing devices. A device is a configuration of machines, each of which performs a specific task, such as washing, reading and cleaning. These devices are used to test human samples to diagnose diseases like cholera, malaria etc. Each test is a job, which is to be processed on these machines for a specific amount of time. Every job has its own pre defined sequence. These samples are to be processed simultaneously on machines owing to constraint that as soon as one machine completes processing a sample, it should be immediately processed by another machine. This constraint is significantly known as no- wait constraint. Given a set of jobs the web application assigns an optimal start time for each job owing to no-wait constraint. This results in reducing the overall time taken to process the jobs, which is formally known as makespan. The main objective of the project is to minimize the makespan. The application is specific to laboratory platform, which helps them to test the samples in optimal time. The heuristic, which I have implemented, is designed with future advancements in mind. The application can be extended to test different heuristic procedures by keeping the time tabling intact. The development environment to be used in this project will require Microsoft Visual Studio, C#, ASP.NET, and other real time chart tools like Microsoft Silverlight.

New algorithms for DNA sequencing by hybridization

The reconstruction of DNA sequences from DNA fragments is one of the most challenging problems in computational biology. In recent years the specific problem of DNA sequencing by hybridization has attracted quite a lot of interest in the optimization community. Despite the fact that well-working constructive heuristics are often the basis for well-working metaheuristics, only two constructive heuristics exist. Both approaches were proposed by Blazewicz and colleagues; the first one is a look-ahead greedy technique, and the second one is a constructive technique based on constructing reliable sub-sequences. Our motivation was twofold. First, we wanted to develop better constructive heuristics. Second, on the basis of these heuristics we wanted to develop new state-of-the-art metaheuristics for DNA sequencing by hybridization. In the first part of the paper we present our constructive heuristics. We show that the results of the best constructive heuristic are comparable to the results of existing metaheuristics, while using less computational time. In the second part of the paper we propose an ant colony optimization (ACO) approach and apply it in a so-called multi-level framework. Both, the ACO algorithm and the multi-level framework are based on our constructive heuristics. The computational results show that our algorithm is currently a state-of-the-art algorithm for DNA sequencing by hybridization.Postprint (published version