AI Medical Compendium Topic:
Databases, Protein

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Computational Methods for Annotation Transfers from Sequence.

Methods in molecular biology (Clifton, N.J.)
Surveys of public sequence resources show that experimentally supported functional information is still completely missing for a considerable fraction of known proteins and is clearly incomplete for an even larger portion. Bioinformatics methods have...

Best Practices in Manual Annotation with the Gene Ontology.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) is a framework designed to represent biological knowledge about gene products' biological roles and the cellular location in which they act. Biocuration is a complex process: the body of scientific literature is large and selec...

Identification of self-interacting proteins by exploring evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix.

Oncotarget
Self-interacting Proteins (SIPs) play an essential role in a wide range of biological processes, such as gene expression regulation, signal transduction, enzyme activation and immune response. Because of the limitations for experimental self-interact...

MSLVP: prediction of multiple subcellular localization of viral proteins using a support vector machine.

Molecular bioSystems
Knowledge of the subcellular location (SCL) of viral proteins in the host cell is important for understanding their function in depth. Therefore, we have developed "MSLVP", a two-tier prediction algorithm for predicting multiple SCLs of viral protein...

Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.

Molecular bioSystems
Protein-protein interactions (PPIs) play a vital role in most biological processes. Hence their comprehension can promote a better understanding of the mechanisms underlying living systems. However, besides the cost and the time limitation involved i...

SAnDReS a Computational Tool for Statistical Analysis of Docking Results and Development of Scoring Functions.

Combinatorial chemistry & high throughput screening
BACKGROUND: Docking allows to predict ligand binding to proteins, since the 3D-structure for the target is available. Several docking studies have been carried out to identify potential ligands for drug targets. Many of these studies resulted in the ...

A novel machine learning method for cytokine-receptor interaction prediction.

Combinatorial chemistry & high throughput screening
Most essential functions are associated with various protein-protein interactions, particularly the cytokine-receptor interaction. Knowledge of the heterogeneous network of cytokine- receptor interactions provides insights into various human physiolo...

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

Journal of biosciences
Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown tha...

Sequence based human leukocyte antigen gene prediction using informative physicochemical properties.

International journal of data mining and bioinformatics
Prediction of different classes within the human leukocyte antigen (HLA) gene family can provide insight into the human immune system and its response to viral pathogens. Therefore, it is desirable to develop an efficient and easily interpretable met...

Exploiting multi-layered vector spaces for signal peptide detection.

International journal of data mining and bioinformatics
Analysing and classifying sequences based on similarities and differences is a mathematical problem of escalating relevance and importance in many scientific disciplines. One of the primary challenges in applying machine learning algorithms to sequen...