Editorial Forward

Jayaraman Valadi

Abstract


With the availability of next generation sequencing technology, there is a tremendous need for development of novel tools, algorithms and methodologies for extracting useful information and knowledge from exponentially growing data.  This need has catalyzed active research in the overlapping fields of Machine Learning (ML) and Artificial Intelligence (AI). First issue of IJCB is bringing some very good research articles with a detailed view of the cutting edge machine learning algorithms.

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References


Vivekanand et al. Accurate Demarcation of Protein Domain Linkers Based on Structural Analysis of Linker Probable Region. IJCB. 2012; Volume 1 (Issue 1): Page 03-13.

Chen et al. Protein Local Tertiary Structure Prediction by Super Granule Support Vector Machines with Chou-Fasman Parameter. IJCB. 2012; Volume 1 (Issue 1): Page 14-27.

Jain et al. TpPred: A Tool for Hierarchical Prediction of Transport Proteins Using Cluster of Neural Networks and Sequence Derived Features. IJCB. 2012; Volume 1 (Issue 1): Page 28-36.

Pugalenthi et al. iFace: A Bioinformatics Tool for the Analysis of Protein-Protein Interface. IJCB. 2012; Volume 1 (Issue 1): Page 37-42.

Vyas et al. Applications of Support Vector Machines as a Robust tool in High Throughput Virtual Screening. IJCB. 2012; Volume 1 (Issue 1): Page 43-55.

Sengupta et al. Application of Support Vector Machines in Virtual Screening. IJCB. 2012; Volume 1 (Issue 1): Page 56-62.