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Sequence Alignment

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Sequence-Based Prediction of Cysteine Reactivity Using Machine Learning.

Biochemistry
As one of the most intrinsically reactive amino acids, cysteine carries a variety of important biochemical functions, including catalysis and redox regulation. Discovery and characterization of cysteines with heightened reactivity will help annotate ...

NFPscanner: a webtool for knowledge-based deciphering of biomedical networks.

BMC bioinformatics
BACKGROUND: Many biological pathways have been created to represent different types of knowledge, such as genetic interactions, metabolic reactions, and gene-regulating and physical-binding relationships. Biologists are using a wide range of omics da...

A novel alignment-free method to classify protein folding types by combining spectral graph clustering with Chou's pseudo amino acid composition.

Journal of theoretical biology
The present work employs pseudo amino acid composition (PseAAC) for encoding the protein sequences in their numeric form. Later this will be arranged in the similarity matrix, which serves as input for spectral graph clustering method. Spectral metho...

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic...

Protein sequence-similarity search acceleration using a heuristic algorithm with a sensitive matrix.

Journal of structural and functional genomics
Protein database search for public databases is a fundamental step in the target selection of proteins in structural and functional genomics and also for inferring protein structure, function, and evolution. Most database search methods employ amino ...

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

PloS one
Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine l...

Detecting false positive sequence homology: a machine learning approach.

BMC bioinformatics
BACKGROUND: Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to ...

Gapped sequence alignment using artificial neural networks: application to the MHC class I system.

Bioinformatics (Oxford, England)
MOTIVATION: Many biological processes are guided by receptor interactions with linear ligands of variable length. One such receptor is the MHC class I molecule. The length preferences vary depending on the MHC allele, but are generally limited to pep...

A Guaranteed Similarity Metric Learning Framework for Biological Sequence Comparison.

IEEE/ACM transactions on computational biology and bioinformatics
Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. The distance and similarity between two sequence are very important and widely studied. During the last decades, Similarity(distance) metric ...

The identification of cis-regulatory elements: A review from a machine learning perspective.

Bio Systems
The majority of the human genome consists of non-coding regions that have been called junk DNA. However, recent studies have unveiled that these regions contain cis-regulatory elements, such as promoters, enhancers, silencers, insulators, etc. These ...