abstract ethanol has a vast consumption around the world. many researches confirmed some adverse effect of this component on human health. in addition, recent studies showed significant alteration in both cellular population, and protein profile of human foreskin fibroblast cell line (hfff2) in the specific dosage of ethanol. here, the role and interaction of some proteins (characterized by sig...

We have developed a method that predicts Protein-Protein Interactions (PPIs) based on the similarity of the context in which proteins appear in literature. This method outperforms previously developed PPI prediction algorithms that rely on the conjunction of two protein names in MEDLINE abstracts. We show significant increases in coverage (76% versus 32%) and sensitivity (66% versus 41% at a sp...

The study of protein-protein interactions (PPIs) and predicting the protein structure plays a critical role in understanding cellular processes designing therapeutic interventions. In this research, we explore application quantum algorithms, specifically Grover’s algorithm, improving accuracy efficiency PPI prediction. By harnessing inherent parallelism search capabilities aim to enhance identi...

Knowledge of protein-protein interactions (PPIs) is important for identifying the functions of proteins and the processes they are involved in. Although data of human PPIs are easily accessible through several public databases, these databases do not specify the human tissues in which these PPIs take place. The TissueNet database of human tissue PPIs (http://netbio.bgu.ac.il/tissuenet/) associa...

Recently, protein-protein interaction prediction (PPIP) has been emerging as an appealing question. Although several in silico approaches have been developed to delineate the potential protein-protein interaction (PPI), there are few online tools of human PPIP for further experimental design. Here we present an online service, hsPPIP (Protein-Protein Interaction Predicting of Homo Sapiens), to ...

Protein-protein interaction (PPIs) is an important part of many life activities in organisms, and the prediction protein-protein interactions closely related to protein function, disease occurrence, treatment. In order optimize performance interactions, here a RT-MOS model was constructed based on Random Forest (RF) Matrix Sequence (MOS) predict interactions. Firstly, MOS used encode sequences ...

Druggable Protein-protein Interaction Assessment System (Dr. PIAS) is a database of druggable protein-protein interactions (PPIs) predicted by our support vector machine (SVM)-based method. Since the first publication of this database, Dr. PIAS has been updated to version 2.0. PPI data have been increased considerably, from 71,500 to 83,324 entries. As the new positive instances in our method, ...

Proteins carry out their function in a cell through interactions with other proteins. A large scale Protein-Protein Interaction (PPI) network of an organism provides static yet an essential structure of interactions, which is valuable clue for understanding the functions of proteins and pathways. PPIs are determined primarily by experimental methods; however, computational PPI prediction method...

The identification and annotation of protein-protein interactions (PPIs) is of great importance in systems biology. Big data produced from experimental or computational approaches allow not only the construction of large protein interaction maps but also expand our knowledge on how proteins build up molecular complexes to perform sophisticated tasks inside a cell. However, if we want to accurat...

Quantitatively detecting correlations of multiple protein-protein interactions (PPIs) in vivo is a big challenge. Here we introduce a novel method, termed Protein-interactome Footprinting (PiF), to simultaneously measure multiple PPIs in one cell. The principle of PiF is that each target physical PPI in the interactome is simultaneously transcoded into a specific DNA sequence based on dimerizat...