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Triptolide is an important active compound derived from Chinese herbal medicine Tripterygium wilfordii Hook f. Despite its positive therapeutic effects, the female reproductive toxicity is still blocking its clinical application with its toxicity mechanism is still obscure. In order to tackle the mechanism of female reproductive toxicity, one intuitive approach is to explore the biological molecule...
Understanding how pathogen's proteins interact with its host's proteins is the key concept for understanding pathogen's infection mechanism, which can lead to the discovery of improved therapeutics for treating infectious diseases. Several studies suggest that proteins from various pathogens tend to interact with human proteins involved in the same biological pathway. This implies that pathogens are...
Protein function annotation is vital for identifying disease causative factors and for solving mysteries behind biological system complexities. As manual annotation requires costly and laborious in vitro methods, in silico protein function prediction is preferred nowadays. According to literature, one in five yeast mitochondrial proteins are known to be human disease related. This paper presents a...
As protein-protein interactions always change with time, environments and different stages of cell cycle, the clustering analysis on static protein-protein interaction (PPI) networks can not reflect this dynamics property and is far from satisfactory. To solve it, this paper proposes a method based on time-sequenced association and Ant Colony Clustering for identifying Protein Complexes in Dynamic...
Interactions between proteins and ligands are relevant in many biological processes. In the last years, such interactions have gained even more attention as the comprehension of protein-ligand molecular recognition is an important step to ligand prediction, target identificantion, and drug design, among others. This article presents GReMLIN (Graph Mining strategy to infer protein-Ligand INteraction...
The phenomenal growth in the healthcare data has inspired us in investigating robust and scalable models for data mining. For classification problems Information Gain(IG) based Decision Tree is one of the popular choices. However, depending upon the nature of the dataset, IG based Decision Tree may not always perform well as it prefers the attribute with more number of distinct values as the splitting...
It is commonly concluded that health literacy focuses on individual skills to obtain, process and understand health information and services necessary to make appropriate health decisions. To achieve this, an individual first needs to obtain an adequate level of health literacy. However, nowadays, the information that individuals encounter with regards to their health, the amount, credibility and...
Effective decision-making to improve healthcare for people depends essentially upon availability of reliable health data. Several developing countries have maternal health indicators lagging behind as compared to international targets set by the UN as Millennium or Sustainable Development Goals. One of the major reasons is poor and non-standardized maternal health record keeping that affect data quality...
Selection of influential genes using gene expression data from normal and disease samples is an important topic in bioinformatics. In this paper, we propose a novel computational method for the problem, which combines gene expression patterns from normal and disease samples with a mathematical model of metabolic networks. This method seeks a set of k genes knockout of which drives the state of the...
In this work, we studied a common problem in Systems Biology, which is the inference or reverse engineering of gene regulatory networks from gene expression data. We addressed this problem using the Boolean formalism, where the expression of a gene is represented only by two possible values: 0 (not expressed) or 1 (expressed). Besides that, our methodology is based on a feature selection approach...
Wilms tumor is one of lethal child renal cancers, for which no known disease causing mechanisms exist. In this paper, we tried to identify possible disease causing microRNA(miRNA)-mRNA pairs (interactions) by analyzing (partially matched) miRNA/mRNA gene expression profiles with the recently proposed principal component analysis based unsupervised feature extraction. It successfully identified multiple...
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