Prediction of Protein Interactions on HIV-1-Human PPI Data using a Novel Closure-based Integrated Approach

  title={Prediction of Protein Interactions on HIV-1-Human PPI Data using a Novel Closure-based Integrated Approach},
  author={K. Mondal and Nicolas Pasquier and A. Mukhopadhyay and C. D. C. Pereira and U. Maulik and A. Tettamanzi},
Discovering Protein-Protein Interactions (PPI) is a new interesting challenge in computational biology. Identifying interactions among proteins was shown to be useful for finding new drugs and preventing several kinds of diseases. The identification of interactions between HIV-1 proteins and Human proteins is a particular PPI problem whose study might lead to the discovery of drugs and important interactions responsible for AIDS. We present the FIST algorithm for extracting hierarchical bi… Expand
Knowledge discovery from HIV-1-human PPIs assimilating interaction keywords
An effective computational approach using pattern-mining based algorithm in order to predict novel interactions between HIV-1 and human proteins based on the experimentally validated interactions curated in public PPI database is presented. Expand
A complete review of computational methods for human and HIV-1 protein interaction prediction
An overview of HIV-1 proteins and their role in virus-replication is given followed by a discussion on different types of antiretroviral drugs and HIV- 1-human PPI database. Expand
A review of in silico approaches for analysis and prediction of HIV-1-human protein-protein interactions
A comparative assessment of these studies and some methodologies for discussing the implication of their results are presented, and different computational techniques for predicting HIV-1-human PPIs are reviewed and a comparative study of their applicability is provided. Expand
Review of computational methods for virus–host protein interaction prediction: a case study on novel Ebola–human interactions
The assessment result shows that the predicted human host proteins are highly similar with known human interaction partners of EBOV in the context of structure and semantics and are responsible for similar biochemical activities, pathways and host–pathogen relationships. Expand
Finding Prediction of Interaction Between SARS-CoV-2 and Human Protein: A Data-Driven Approach
In this study, an approach was presented for predicting novel interactions from maximal biclusters and a study was conducted on the gene ontology and KEGG-pathway in relation to the newly predicted interactions. Expand
Computational approaches for prediction of pathogen-host protein-protein interactions
An overview of the computational approaches for predicting PHI systems, discussing their weakness and abilities, with future directions is presented. Expand
Mining of Association Rules from HIV-1 Protein Data
Rules based on the diagonal and the off-diagonal motifs present in the matrices are extracted in order to predict HIV-1 protease data and are proposed to generate frequent itemsets from machine learning algorithm like Apriori. Expand
Prediction of host-pathogen protein interactions by extended network model
Empirical results showed that integrating the host and pathogen interactions yields better performance consistently in almost all experiments, and the truepositive rate of the predictions was expected to increase. Expand
A new sequence based encoding for prediction of host-pathogen protein interactions
A novel and robust sequence based feature extraction method, named Location Based Encoding, to predict pathogen-host interactions with machine learning based algorithms and compares its method with sequence based protein encoding methods, which are widely used in the literature. Expand
Algorithms for Data Mining and Bio-informatics
This thesis work proposes an original approach for extracting different categories of knowledge patterns while using minimum number of resources, named FIST for Frequent Itemset mining using Suffix-Trees, based on a new suffix-tree data structure that enables the efficient storage of data and computation of relevant patterns in primary memory. Expand


Mining association rules from HIV-human protein interactions
This article has predicted some new viral-human interactions based on the discovered association rules and identified a set of association rules among the human proteins with high confidence. Expand
Prediction of Interactions Between HIV-1 and Human Proteins by Information Integration
This work is the first attempt to predict the global set of interactions between HIV-1 and human host cellular proteins and proposes a supervised learning framework, where multiple information data sources are utilized. Expand
Cataloguing the HIV type 1 human protein interaction network.
This database represents a unique and continuously updated scientific resource for understanding HIV-1 replication and pathogenesis to assist in accelerating the development of effective therapeutic and vaccine interventions. Expand
Kernel methods for predicting protein-protein interactions
The ability of the proposed pairwise kernel method to make accurate predictions despite the sizeable fraction of false positives that are known to exist in interaction databases is demonstrated. Expand
Information assessment on predicting protein-protein interactions
This analysis shows that the MIPS and Gene Ontology functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. can give highly accurate classifications. Expand
A mixture of feature experts approach for protein-protein interaction prediction
The Mixture-of-Feature-Experts method is applied to predict the set of interacting proteins in yeast and human cells and improved upon the best previous methods for this task. Expand
Predicting co-complexed protein pairs using genomic and proteomic data integration
It is demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP) pairs from other characteristics and provide testable hypotheses for experimental validation. Expand
Human immunodeficiency virus type 1, human protein interaction database at NCBI
The ‘Human Immunodeficiency Virus Type 1 (HIV-1), Human Protein Interaction Database’, available through the National Library of Medicine at, was createdExpand
A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data
This work develops an approach using Bayesian networks to predict protein-protein interactions genome-wide in yeast, and observes that at given levels of sensitivity, the predictions are more accurate than the existing high-throughput experimental data sets. Expand
Integrated Bio-Entity Network: A System for Biological Knowledge Discovery
It is shown that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. Expand