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Calcium channel blockers (CCB) disrupt the movement of calcium and prevent it from entering cells of the blood vessel walls. They are used to widen blood vessel resulting in lower blood pressure. Amlodipine is one such calcium channel blocker that dilates the blood vessel and improves blood flow. It is used to treat angina, high blood pressure and hypertension. Amlodipine is quite effective in treating...
Protein-protein interactions (PPI) occur at every level of cell functions. The identification of protein interactions provides a global picture of cellular functions and biological processes. It is also an essential step in the construction of PPI networks for human and other organisms. PPI prediction has been considered a promising alternative to the traditional drug design techniques. The identification...
Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts could improve the performance of de novo protein structure prediction methods. In this study, a novel method based on learning-to-rank (RRCRank) has been presented to predict protein...
Prediction of Protein-RNA binding sites is one of the most challenging and intriguing problems in the field of computational biology. Here, we proposed an effectively machine learning algorithm termed PredRBR (Prediction of RNA Binding Residues), using Gradient Tree Boosting algorithm and mRMR-IFS feature selection method in combination with sequence features, structure characteristics and two categories...
Proteins can be classified among the four structural classes of All-Alpha, All-Beta, Alpha+Beta and Alpha/Beta which are further subdivided into 27 folds. Protein fold classification problem is cited in the literature as a challenging unbalanced classification problem with the accuracy results being as low as 51.1% on the bench mark data set of Ding et al. and highest accuracy at 60.5% using 2500...
The efficiency research about protein sub-cellular localization has become a hot topic recently. Feature extraction plays an important role in the accurate classification or location of proteins. Since the contribution of each feature dimension is different, this paper enlarges the contribution of feature dimensions which have great effect on classification by weighting with its Fisher linear discriminant...
Gene regulation in eukaryotes is a very complicated and myriad procedure. It is a diverse action which include finding the protein coding regions, locating transcription factor binding sites, promoter identification and determination of cis and trans regulatory elements. Transcription factor binding prediction is very costly using experimental techniques. So computational methods can be used for prediction...
With the explosion of protein sequences generated in the Post-Genomic Age, it is urgent to develop an automated method to predict protein quaternary structure. To explore this problem, we adopted an approach based on a sequence encoding descriptor by fusing PseAA (Pseudo Amino Acid) and DC (Dipeptide Composition) representing a protein sample. Here, a completely different approach, manifold learning...
MicroRNAs are one type of noncoding RNA that regulate their target mRNAs before mRNAs are translated into proteins. Although it has been demonstrated that the regulation is through partial binding of the seed region of a miRNA and its targets, the mechanism of this process is not fully discovered. Some biological experiments have shown that even perfect base pairing in the seed region does not always...
New technological advances in large-scale protein-protein interaction (PPI) detection provide researchers a valuable source for elucidating the bimolecular mechanism in the cell. In this paper, we investigate the problem of protein complex detection from noisy protein interaction data, i.e., finding the subsets of proteins that are closely coupled via protein interactions. Many people try to solve...
Protein secondary structure prediction is a fundamental and important component in the analytical study of protein structure and functions. Using the pseudo amino acid (PseAA) composition to represent the sample of a protein can incorporate a considerable amount of sequence pattern information so as to improve the prediction quality for its structural or functional classification. In this paper, the...
In this paper, a system based on the novel Maximum Variance Projection (MVP) is proposed to improve the performance of protein subcellular localization prediction. Firstly, the protein sequences are quantized into a high dimension space using a new representation approach Position-Specific Score Matrix (PSSM). However, the problems caused by such representation are computation complexity and complicated...
The membrane protein type is an important feature in characterizing the overall topological folding type of a protein or its domains therein. How to fast and efficiently annotate the type of an uncharacterized membrane protein is a challenge. Some discrete models, such as DC (dipeptide composition) have been proposed to represent a protein sequence in the field of predicting membrane protein types...
Predicting gene function is usually formulated as binary classification problem. However, we only know which gene has some function while we are not sure that it doesn't belong to a function class, which means that only positive examples are given. Therefore, selecting a good training example set becomes a key step. In this paper, we cluster the genes on integrated weighted graph by generalizing the...
Knowing type of an uncharacterized membrane protein often provides a useful clue in both basic research and drug discovery. With the explosion of protein sequences generated in the post genomic era, determination of membrane proteins types by experimental methods is expensive and time consuming. It therefore becomes important to develop an automated method to find the possible type of membrane protein...
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