Computational biology is the application of software engineering, statistics, and mathematics to problems in biology. Computational biology compasses an extensive variety of fields in science, including genomics/hereditary qualities, biophysics, cell science, biochemistry, and evolution. Moreover, it makes utilization of apparatuses and strategies from numerous distinctive quantitative fields, including algorithm design, machine learning and statistical physics. Much of computational science is concerned with the examination of atomic information, for example, biosequences (DNA, RNA, or protein groupings), three-dimensional protein structures, gene expression data, or molecular biological networks (metabolic pathways, protein-protein interaction networks, or gene regulatory networks). The terms computational science and bioinformatics are regularly utilized reciprocally. Be that as it may, computational science off and on again means the improvement of calculations, numerical models, and systems for statistical inference, while bioinformatics is more connected with the advancement of programming devices, databases, and visualization strategies.
Innovations are new idea, device or process. Innovations are the application of better solutions that meet new requirements, inarticulate needs or existing market needs. It is proficient through more effective products, processes, services, technologies, or new ideas that are readily available to markets, governments and society. Innovations are something original and novel, as a significant, new that âbreaks intoâ the market or society.
The Journal of Computer Science & Systems Biology includes a wide range of fields in its discipline to create a platform for the authors to make their contribution in the form of review, research, mini-review, short communication etc towards the journal and the editorial office promises a peer review process for the submitted manuscripts for the quality of publishing.
Last date updated on September, 2014