Current Bioinformatics - Volume 11, Issue 5, 2016

Background: The performance of the text classification techniques is commonly affected by the characteristics and representation of the document corpora itself. Of all the problems arising from the corpus, there are three major difficulties which the classifiers must deal with: the feature selection issues, the class imbalance problem and the size of the training set. Objective: The objective of this paper is to present a novel Read More

Background: One of the means to increase in-field crop yields is the use of software tools to predict future yield values using past in-field trials and plant genetics. The traditional, statistics-based approaches lack environmental data integration and are very sensitive to missing and/or noisy data. Objective: In this paper, we show that a cooperative, adaptive Multi-Agent System can overcome the drawbacks of such algorithms. Met Read More

Background: The combination of antimicrobial products is a promising biomedical strategy against the ever growing number of resistant strains emerging in healthcare and community settings. Agents with alternative modes of action, such as antimicrobial peptides (AMPs), and the efficacy of combined actions are being evaluated. Despite the availability of various antimicrobial data repositories, a wealth of information remain Read More

Background: In cases where only a single group (or class) of samples is available for a given problem, positive unlabeled learning algorithms can be applied. One such case is the interactions between various biological/chemical entity pairs, where only the set of interacting entities can be collected, not the “noninteracting” ones. Objective: We aim to improve the performance of deriving protein-protein and protein-ligand in Read More

Background: It has been noticed that the conventional approaches of vaccinology are highly successful to bring down the rate of disease incidences of life threatening infections in 20th century. But these approaches certainly suffer with some delimitation. Such as they take decades to unravel pathogens and antigens related to a disease and even then only few but not all of the antigens are disclosed. Therefore, persistent need Read More

Background: The choice of a bioinformatics tool that is used to design and analyse bioinformatics models is usually influenced by the choice of format used to store the models on the hard drive and vice versa and may seem irrelevant to researchers who design and analyse biological models using high-level computer software. However, the method for saving created models, which is usually opaque to users, can have Read More

Background: Tumor classification is one of the most important applications of gene expression data. Due to high dimensionality in microarray data, dimensionality reduction plays a crucial role in tumor classification based on gene expression profiles. Objective: The primary objective of this study is to increase the accuracy of tumor classification by reducing the dimensionality of gene expression data with feature extraction metho Read More

Background: RNA molecules play several fundamental roles in any living organism. The function of an RNA molecule is highly related to its three dimensional conformation which is referred to as RNA tertiary structure. Since the experimental determination or computational prediction of the RNA tertiary structure is very complicated, tremendous efforts have been focused on the relatively simple RNA secondary structure. Obj Read More

Background: Crosstalk is the phenomenon in which two or more biochemical pathways interact with each other. In the presence of many inputs (cross talk) to a signaling pathway, there is a high chance of getting it excess activation. Therefore, to put a ‘brake’ over excessive activation, it has to put extra efforts in the form of regulatory loops. Objective: Design the crosstalk modeling study to analyze the effect of crosstalk on a Read More

Background: Analysis on classification of microarray gene expression data has been an important research topic in bioinformatics. Objective: For the unsatisfied performance of basic classification methods, researches on ensemble classifiers prove ensembling classifiers to be an efficient way to increase classification accuracy. Method: In this paper, we propose a new diversity-based classification method, which combines a fea Read More