The Protein Data Bank (PDB) undergoes an exponential expansion in terms of the number of macromolecular structures deposited every year. A pivotal question is how this rapid growth of structural information improves the quality of three-dimensional models constructed by contemporary bioinformatics approaches. To address this problem, we performed a retrospective analysis of the structural cover...

MOTIVATION The correct identification of translation initiation sites (TIS) remains a challenging problem for computational methods that automatically try to solve this problem. Furthermore, the lion's share of these computational techniques focuses on the identification of TIS in transcript data. However, in the gene prediction context the identification of TIS occurs on the genomic level, whi...

Finding similarity between a pair of protein structures is one of the fundamental tasks in many areas of bioinformatical research such as protein structure prediction, function mapping, etc. We propose a method for finding pairing of amino acids based on densities of the structures and we also propose a modification to the original template modeling-score (TM-Score) rotation algorithm that asse...

Bioinformatics, which has developed rapidly in recent years with the collaborative contributions of fields biology and informatics, provides a deeper perspective on analysis understanding complex biological data. In this regard, bioinformatics an interdisciplinary background rich literature terms domain-specific studies. Providing holistic picture research by analyzing major topics their trends...

Chloroflexus aurantiacus J-10-f1 is an anoxygenic, photosynthetic, facultative autotrophic gram negative bacterium found from hot spring at a temperature range of 50-60°C. It can sustain itself in dark only if oxygen is available thereby exhibiting a dark orange color, however display a dark green color when grown in sunlight. Genome of the organism contains total of 3853 proteins out ...

In this work, we describe the protein secondary structure prediction module of a distributed bio-informatics system. Protein databases contain over a million of sequenced proteins, however there is structuring information for at most 2% of that number. The challenge is to reliably predict the structure based on classifiers. Our contribution is the evaluation of architectures of multiple classif...

Abstract Introduction: Estrogen receptor-positive (ER-positive) breast cancer is a subgroup of breast tumors that is more likely to respond to hormone therapy. ER-positive and ER- negative breast cancers tend to show different patterns of metastasis because of different signaling cascade and genes that are activated by estrogen response. Genetic factors can contribute to high rates of metastas...

Abstract Introduction: Estrogen receptor-positive (ER-positive) breast cancer is a subgroup of breast tumors that is more likely to respond to hormone therapy. ER-positive and ER- negative breast cancers tend to show different patterns of metastasis because of different signaling cascade and genes that are activated by estrogen response. Genetic factors can contribute to high rates of metastas...

Prediction accuracy is an essential topic to be researched and studied to have maximum precision and more efficient prediction systems especially in critical fields like medicine and bioinformatics. In this study we investigated the prediction models, viz., Logistic Regression, Neural Network and Decision Tree and compared their prediction performance taking into account the dataset size and th...

Most of the problems in bioinformatics are now the challenges in computing. This paper aims at building a classifier based on Multiple Attractor Cellular Automata (MACA) which uses fuzzy logic. It is strengthened with an artificial Immune System Technique (AIS), Clonal algorithm for identifying a protein coding and promoter region in a given DNA sequence. The proposed classifier is named as AIS...