AI Medical Compendium Topic

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Sequence Analysis, Protein

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DiagnoProt: a tool for discovery of new molecules by mass spectrometry.

Bioinformatics (Oxford, England)
MOTIVATION: Around 75% of all mass spectra remain unidentified by widely adopted proteomic strategies. We present DiagnoProt, an integrated computational environment that can efficiently cluster millions of spectra and use machine learning to shortli...

ISPRED4: interaction sites PREDiction in protein structures with a refining grammar model.

Bioinformatics (Oxford, England)
MOTIVATION: The identification of protein-protein interaction (PPI) sites is an important step towards the characterization of protein functional integration in the cell complexity. Experimental methods are costly and time-consuming and computational...

SChloro: directing Viridiplantae proteins to six chloroplastic sub-compartments.

Bioinformatics (Oxford, England)
MOTIVATION: Chloroplasts are organelles found in plants and involved in several important cell processes. Similarly to other compartments in the cell, chloroplasts have an internal structure comprising several sub-compartments, where different protei...

Learning Parameter-Advising Sets for Multiple Sequence Alignment.

IEEE/ACM transactions on computational biology and bioinformatics
While the multiple sequence alignment output by an aligner strongly depends on the parameter values used for the alignment scoring function (such as the choice of gap penalties and substitution scores), most users rely on the single default parameter...

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...

The importance of physicochemical characteristics and nonlinear classifiers in determining HIV-1 protease specificity.

Bioengineered
This paper reviews recent research relating to the application of bioinformatics approaches to determining HIV-1 protease specificity, outlines outstanding issues, and presents a new approach to addressing these issues. Leading machine learning theor...

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

IEEE/ACM transactions on computational biology and bioinformatics
Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can furt...

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...

Granular support vector machine to identify unknown structural classes of protein.

International journal of data mining and bioinformatics
To date, classification of structural class using local protein structure rather than the whole structure has been gaining widespread attention. It is noted that the structural class lies in local composition or arrangement of secondary structure, wh...