Beware of External Validation! - A Comparative Study of Several Validation Techniques used in QSAR Modelling.

Background: Proper validation is an important aspect of QSAR modelling. External validation is one of the widely used validation methods in QSAR where the model is built on a subset of the data and validated on the rest of the samples. However, its effectiveness for datasets with a small number of samples but a large number of predictors remains suspect.

A Bioinformatics approach to designing a Zika virus vaccine.

The Zika virus infections have reached epidemic proportions in the Latin American countries causing severe birth defects and neurological disorders. While several organizations have begun research into design of prophylactic vaccines and therapeutic drugs, computer assisted methods with adequate data resources can be expected to assist in these measures to reduce lead times through bioinformatics approaches. Using 60 sequences of the Zika virus envelope protein available in the GenBank database, our analysis with numerical characterization techniques and several web based bioinformatics servers identified four peptide stretches on the Zika virus envelope protein that are well conserved and surface exposed and are predicted to have reasonable epitope binding efficiency.

Mathematical descriptors for the prediction of property, bioactivity, and toxicity of chemicals from their structure: a chemical-cum-biochemical approach.

This review article covers major aspects of mathematical chemistry, QSAR, chemoinformatics, bioinformatics, and molecular modeling research carried out by Subhash C. Basak and coworkers during 1968 to the present time in three distinct phases: 1) Department of Biochemistry, University of Calcutta and Charuchandra College, India (1968-1981); 2) Department of Chemistry & Biochemistry, University of Minnesota, Duluth, USA (1982-1987), and 3) Natural Resources Research Institute, University of Minnesota, Duluth, UMD-NRRI (1988-date). Topics discussed include development of novel mathematical descriptors of molecules and biomolecules; QSAR, HiQSAR, DiffQSAR and I-QSAR studies using chemodescriptors and biodescriptors; formulation of arbitrary quantitative molecular similarity analysis (QMSA) and tailored QMSA methods and their applications.

Adapting interrelated two-way clustering method for quantitative structure-activity relationship (QSAR) modeling of mutagenicity/non- mutagenicity of a diverse set of chemicals.

Interrelated Two-way Clustering (ITC) is an unsupervised clustering method developed to divide samples into two groups in gene expression data obtained through microarrays, selecting important genes simultaneously in the process. This has been found to be a better approach than conventional clustering methods like K-means or selforganizing map for the scenarios when number of samples is much smaller than number of variables (n«p). In this paper we used the ITC approach for classification of a diverse set of 508 chemicals regarding mutagenicity.