Jump to ContentJump to Main Navigation
Navigate here

Development and Applications of Novel Methods in Computational Biology

                                  ◄ Back to journal

GUEST EDITORS:

Lin Li, University of Texas at El Paso (lead)
Marat Talipov
, New Mexico State University
Sangjin Kim
, University of Texas at El Paso
Yi He
, University of New Mexico

DESCRIPTION

Because of the fast developments of computer hardware and computational algorithms, computational biology has become a significant approach to understand the biological phenomena. Computational methods provide many details in wide range scales of space and time, which help to better understand experimental data and predict more information. During the last couple of decades, numerous novel computational models and packages have been developed and improved. Such computational tools have been widely used in many fields, such as drug design, protein structure prediction, protein-protein complex structure prediction, simulations of biomolecules, etc. To assess the current algorithms, several blind prediction challenges are provided periodically: Grand Challenge from D3R (Drug Design Data Resource) aims to test and improve the drug design algorithms; CASP (Critical Assessment of Structure Prediction) aims to access the protein structure prediction algorithms; CAPRI (Critical Assessment of PRediction of Interactions) aims to access protein-protein complex prediction models; pKa-cooperative  aims to provide a forum for improving the pKa predictions, etc. These blind tests, as well as many other evidences, demonstrate that the computational biology algorithms and models are getting more accurate and powerful. To document various advances in the field, the journal Computational and Mathematical Biophysics will publish a special issue on “Development and applications of novel methods in computational biology”.

As a recently established journal, Computational and Mathematical Biophysics (CMB), https://www.degruyter.com/view/j/cmb, is the formal continuation of Molecular Based Mathematical Biology, published by De Gruyter. The mission of CMB is to publish the highest quality work that promotes the development of theoretical formulations, mathematical models, numerical algorithms, and computational techniques for elucidating molecular mechanisms and for solving open problems at the forefront of molecular bioscience and biophysics.

SCOPE

Original papers and high-quality review articles are solicited for this special issue. Potential topics include, but are not limited to:

  • Structural determination and molecular shape analysis of molecules
  • Protein-protein interactions
  • Prediction of ligand-protein interaction energies
  • Geometric and topological modeling of macromolecules
  • Structure Alignment of macromolecules
  • Drug design
  • Molecule-related software or database development
  • Machine learning and data mining in molecular big data
  • Algorithms, analysis and validation for bio-molecular data
  • Single cell sequencing data analysis

HOW TO SUBMIT

Before submission authors should carefully read over the author guidelines, which are located at https://www.degruyter.com/view/j/cmb. All manuscripts are subject to the standard peer review process before publication. Please note the publisher has waived the Article Processing Charges for this special issue, but articles will be open-access in accordance with the overall goals of the journal. Prospective authors should submit their manuscript on line at http://mlbmb.edmgr.com/

When entering your submission (via online submission system), please choose the option Special Issue Develop. Appl. Novel Meth. Comput. Biol.

Important Dates:
Manuscript Due August 1st, 2019;
First round of reviews September 15th, 2019;
Anticipated publication date: December 1st, 2019.

We are looking forward to your submission!

If you have any questions, please contact Dr. Lin Li at: lli5@utep.edu, or the Editorial Office at Cmb.Editorial@degruyter.com