NoVaTeST: identifying genes with location-dependent noise variance in spatial transcriptomics data.

Motivation: Spatial transcriptomics (ST) can reveal the existence and extent of spatial variation of gene expression in complex tissues. Such analyses could help identify spatially localized processes underlying a tissue's function. Existing tools to detect spatially variable genes assume a constant noise variance across spatial locations.

Antigenic: An improved prediction model of protective antigens.

An antigen is a protein capable of triggering an effective immune system response. Protective antigens are the ones that can invoke specific and enhanced adaptive immune response to subsequent exposure to the specific pathogen or related organisms. Such proteins are therefore of immense importance in vaccine preparation and drug design.

DPP-PseAAC: A DNA-binding protein prediction model using Chou's general PseAAC.

A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification of DNA-BPs using experimental methods is expensive as well as time consuming. As such, fast and accurate computational methods are sought for predicting whether a protein can bind with a DNA or not.

isGPT: An optimized model to identify sub-Golgi protein types using SVM and Random Forest based feature selection.

The Golgi Apparatus (GA) is a key organelle for protein synthesis within the eukaryotic cell. The main task of GA is to modify and sort proteins for transport throughout the cell. Proteins permeate through the GA on the ER (Endoplasmic Reticulum) facing side (cis side) and depart on the other side (trans side).

Gene selection for cancer classification with the help of bees.

Background: Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it.