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DNA replication, a critical step in cell division and proliferation, is a process of producing two identical replicas from one original DNA molecule. Although great advances have been made in DNA replication research, the detailed mechanism of DNA replication is still unresolved. Faithful DNA replication requires the cooperation of many proteins. Failures in DNA replication leave mutations in the...
Oxidative stress can damage major cell components, including protein, DNA, lipid and cell membranes, which may make cells lose function and induce a wide variety of diseases. As an extensive kind of antioxidants in human and animals, antioxidant proteins are essential to eliminate cell damage and aging problems caused by oxidative stress. Accurate identification of antioxidant proteins is a significant...
Contemporary molecular biology deals with a wide and heterogeneous set of measurements to model and understand underlying biological processes including complex diseases. Machine learning provides a frequent approach to build such models. However, the models built solely from measured data often suffer from overfitting, as the sample size is typically much smaller than the number of measured features...
Protein sub network biomarkers for 144 diseases and pathways are analyzed in terms of protein-protein interaction (PPI) score available in STRING database. Most of the sub network biomarker (SNB) studies are to classify disease samples from the control. But no de novo algorithm is available to identify SNB from the whole genome PPI network without the knowledge of differentially expressed genes. Recently,...
Long non-coding RNAs (lncRNAs) have been implicated in various biological processes, and are linked in many dysregulations. Researchers have reported large number of lncRNA associated human diseases over the past decade. In this article we employed the Non-negative Matrix Factorization method to develop a low-dimensional computational model that can describe the existing knowledge about lncRNA-disease...
Various statistical and machine learning based algorithms have been proposed in literature for selecting an informative subset of genes from micro array data sets. The recent trend is to use functional knowledge to aid the gene selection process. In this paper we propose a clustering algorithm which generates multiple views (clusters) from the micro array expression profiles, each representing a particular...
Newcastle disease (ND) is one of the most serious infectious diseases of poultry, which have an important economic impact on poultry sector production. The causative agent of the disease is Newcastle disease virus (NDV). NDV strains can be classified into two types according to virulence, namely highly virulent (velogenic) and low virulent (lentogenic) based on their pathogenicity in chickens. In...
Breast cancer is the number one killer disease among women worldwide. Although this disease may affect women and men but the rate of incidence and number of deaths are high among women compared to men. Early detection of breast cancer helps to increase the chance of survival since early treatment can be decided for the patients who suffer from this disease. The advent of the Microarray Technology...
Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease causing a progressive loss of motor neurons. The disease prevalence is 5 per 100,000 people. There is no cure and it leads generally to death from respiratory failure in approximately 3-5 years after the first symptoms. The exact causes of the disease are still unknown, however, almost 20% of the known cases have shown gene mutations...
Breast cancer is a complex disease with heterogeneity between patients regarding prognosis and treatment response. Recent progress in advanced molecular biology techniques and the development of efficient methods for database mining lead to the discovery of promising novel biomarkers for prognosis and prediction of breast cancer. In this paper, we applied three computational algorithms (RFE-LNW, Lasso...
In this work, we analyze and evaluate different strategies for comparing Feature Selection (FS) schemes on High Dimensional (HD) biomedical datasets (e.g. gene and protein expression studies) with a small sample size (SSS). Additionally, we define a new feature, Robustness, specifically for comparing the ability of an FS scheme to be invariant to changes in its training data. While classifier accuracy...
Influenza is one of the most important emerging and reemerging infectious diseases, causing high morbidity and mortality in communities (epidemic) and worldwide (pandemic). Here, Classification of human vs. non-human influenza, and subtyping of human influenza viral strains virus is done based on Profile Hidden Markov Models. The classical ways of determining influenza viral subtypes depend mainly...
To construct biologically interpretable features and facilitate Muscular Dystrophy (MD) sub-types classification, we propose a novel integrative scheme utilizing PPI network, functional gene sets information, and mRNA profiling. The workflow of the proposed scheme includes three major steps: First, by combining protein-protein interaction network structure and gene co-expression relationship into...
Conotoxins show prospects for being potent pharmaceuticals in the treatment of some serious disease. Accurate prediction of conotoxin superfamily would have many important applications in biological research and clinical medicine. In this study, we propose a novel dHKNN method to predict conotoxin superfamily. Firstly, we extract the protein's sequential features composed of physicochemical properties,...
HIV is human immunodeficiency virus causes AIDS (acquired immunodeficiency syndrome) which leads to life threatening opportunistic infections. HIV-1 has three groups M, N, O known worldwide. Group M is widely distributed as it has nine subtypes and circulating recombinant forms are also developed due to rapid recombination and mutation. They play an important role in diagnosing the correct group of...
The MMPs and ADAMs are cell surface proteases which belong to metalloprotease family. They play an important role in skin aging, skin disorders, anticancer therapy and other physiological disorders. Thus there arises the need to understand the relationships among various parameters of these proteins for prediction of their classes, structures and functionality. The computational approaches for prediction...
Gene expression data possess two main features: small samples and high dimensions. There are many difficulties on analyzing gene expression data using the traditional machine learning methods. In this paper we use an SVM-RFE based method to obtain the set of trait genes that are related to the disease-resistance property in rice and evaluate these genes according to some heuristics. And then we query...
Selecting differentially expressed genes (DEGs) is one of the most important tasks in microarray applications. However, the sample sizes typically used in current cancer studies may only partially reflect the widely altered gene expressions in cancers. By analyzing three large cancer datasets, we show that, in each cancer, a wide range of functional modules are altered and have high disease classification...
The OpenBiomind toolkit is used to apply GA, GP and local search methods to analyze a large SNP dataset concerning late-onset Alzheimer's disease (LOAD). Classification models identifying LOAD with statistically significant accuracy are identified, and ensemble-based important features analysis is used to identify brain genes related to LOAD, most notably the solute carrier gene SLC6A15. Ensemble...
Hepatitis C virus infection remains a public health problem within an international scope, and much efforts has been devoted to understanding the interaction within HCV and human protein complex. Among several attempts, identification of binding site and prediction of critical residue contribute significantly to the function of a protein, and can narrow the search space required by docking algorithms...
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