Protein stability: a single recorded mutation aids in predicting the effects of other mutations in the same amino acid site.

Motivation: Accurate prediction of protein stability is important for understanding the molecular underpinnings of diseases and for the design of new proteins. We introduce a novel approach for the prediction of changes in protein stability that arise from a single-site amino acid substitution; the approach uses available data on mutations occurring in the same position and in other positions. Our algorithm, named Pro-Maya (Protein Mutant stAbilitY Analyzer), combines a collaborative filtering baseline model, Random Forests regression and a diverse set of features.

MuD: an interactive web server for the prediction of non-neutral substitutions using protein structural data.

The discrimination between functionally neutral amino acid substitutions and non-neutral mutations, affecting protein function, is very important for our understanding of diseases. The rapidly growing amounts of experimental data enable the development of computational tools to facilitate the annotation of these substitutions. Here, we describe a Random Forests-based classifier, named Mutation Detector (MuD) that utilizes structural and sequence-derived features to assess the impact of a given substitution on the protein function.

Mutations of JAK2 in acute lymphoblastic leukaemias associated with Down's syndrome.

Background: Children with Down's syndrome have a greatly increased risk of acute megakaryoblastic and acute lymphoblastic leukaemias. Acute megakaryoblastic leukaemia in Down's syndrome is characterised by a somatic mutation in GATA1. Constitutive activation of the JAK/STAT (Janus kinase and signal transducer and activator of transcription) pathway occurs in several haematopoietic malignant diseases.

A hierarchical protein folding scheme based on the building block folding model.

The building block protein folding model states that the native protein structure is the product of a combinatorial assembly of relatively structurally independent contiguous parts of the protein that possess a hydrophobic core, i.e., building blocks (BBs).

A permissive secondary structure-guided superposition tool for clustering of protein fragments toward protein structure prediction via fragment assembly.

Motivation: Secondary-Structure Guided Superposition tool (SSGS) is a permissive secondary structure-based algorithm for matching of protein structures and in particular their fragments. The algorithm was developed towards protein structure prediction via fragment assembly.

Results: In a fragment-based structural prediction scheme, a protein sequence is cut into building blocks (BBs).