Large volume of Genomics data is produced on daily basis due to the advancement in sequencing technology. This data is of no value if it is not properly analysed. Different kinds of analytics are required to extract useful information from this raw data. Classification, Prediction, Clustering and Pattern Extraction are useful techniques of data mining. These techniques require appropriate selec...

Secondary structure prediction methods are widely used bioinformatics algorithms providing initial insights about protein structure from sequence information. Significant efforts to improve the prediction accuracy over the past years were made, specially the incorporation of information from multiple sequence alignments. This motivated the search for the factors contributing for this improvemen...

Highlights of the IMA workshop RNA in Biology, Bioengineering, and Biotechnology are summarized, including recent developments in RNA secondary structure prediction and RNA design, innovative mathematical constructs for RNA structure, bioinformatics advances in RNA structure analysis and prediction, and experimental progress in RNA folding and imaging. In small things considered is the world re...

MOTIVATION Laboratory RNA structure determination is demanding and costly and thus, computational structure prediction is an important task. Single sequence methods for RNA secondary structure prediction are limited by the accuracy of the underlying folding model, if a structure is supported by a family of evolutionarily related sequences, one can be more confident that the prediction is accura...

Research in protein structure and function is one of the most important subjects in modern bioinformatics and computational biology. It often uses advanced data mining and machine learning methodologies to perform prediction or pattern recognition tasks. This paper describes a new method for prediction of protein secondary structure content based on feature selection and multiple linear regress...

IMAN is an open-source R package that offers users to reconstruct Interlog Protein Network (IPN) integrated from several Protein-protein Interaction Networks (PPIN). Users can overlay different PPINs to mine conserved common network between diverse species. Currently STRING database is applied to extract PPINs with all experimental and computational interaction prediction methods. IMAN helps to...

We consider unsupervised partitioning problems based explicitly or implicitly on the minimization of Euclidean distortions, such as clustering, image or video segmentation, and other change-point detection problems. We emphasize on cases with specific structure, which include many practical situations ranging from meanbased change-point detection to image segmentation problems. We aim at learni...

Protein structure prediction is considered to be the holy grail of bioinformatics. Ab initio and homology modelling are two important groups of methods used in protein structure prediction. Amongst these, ab initio methods assume that no previous knowledge about protein structures is required. On the other hand homology modelling is based on sequence similarity and uses information such as clas...

Subcellular location prediction of proteins is an important and well-studied problem in bioinformatics. This is a problem of predicting which part in a cell a given protein is transported to, where an amino acid sequence of the protein is given as an input. This problem is becoming more important since information on subcellular location is helpful for annotation of proteins and genes and the n...

Protein secondary structures prediction (PSSP) is considered as a challenging task in bioinformatics. Many approaches have been proposed in last few decades in order to solve this problem. Despite the enhancements achieved, the prediction accuracy still remains limited. Accurate prediction of the secondary structure of proteins is a critical step in deducing tertiary structure of proteins and t...