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Protein Interaction Maps

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Identification of distinct blood-based biomarkers in early stage of Parkinson's disease.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Parkinson's disease (PD) is a slowly progressive geriatric disease, which can be one of the leading causes of serious socioeconomic burden in the aging society. Clinical trials suggest that prompt treatment of early-stage Parkinson's disease (EPD) ma...

DeepEP: a deep learning framework for identifying essential proteins.

BMC bioinformatics
BACKGROUND: Essential proteins are crucial for cellular life and thus, identification of essential proteins is an important topic and a challenging problem for researchers. Recently lots of computational approaches have been proposed to handle this p...

System-level responses to cisplatin in pro-apoptotic stages of breast cancer MCF-7 cell line.

Computational biology and chemistry
Cisplatin ceases cell division and induces apoptosis in cancer cell lines. It is well established that cisplatin alters the expression of many genes involved in several cellular processes and pathways including transcription, p53 signaling pathway, a...

Identification of genes of four malignant tumors and a novel prediction model development based on PPI data and support vector machines.

Cancer gene therapy
Triple-negative breast cancer (TNBC), colon adenocarcinoma (COAD), ovarian cancer (OV), and glioblastoma multiforme (GBM) are common malignant tumors, in which significant challenges are still faced in early diagnosis, treatment, and prognosis. There...

Artificial Intelligence Approach To Investigate the Longevity Drug.

The journal of physical chemistry letters
Longevity is a very important and interesting topic, and has been demonstrated to be related to longevity. We combined network pharmacology, machine learning, deep learning, and molecular dynamics (MD) simulation to investigate potent lead drugs. Re...

Using deep maxout neural networks to improve the accuracy of function prediction from protein interaction networks.

PloS one
Protein-protein interaction network data provides valuable information that infers direct links between genes and their biological roles. This information brings a fundamental hypothesis for protein function prediction that interacting proteins tend ...

Protein complex identification based on weighted PPI network with multi-source information.

Journal of theoretical biology
Proteins form complexes to accomplish biological functions such as transcription of DNA, translation of mRNA and cell growth. Detection of protein complexes from protein-protein interaction (PPI) networks is the first step for the analysis of biologi...

A novel matrix of sequence descriptors for predicting protein-protein interactions from amino acid sequences.

PloS one
Protein-protein interactions (PPIs) play an important role in the life activities of organisms. With the availability of large amounts of protein sequence data, PPIs prediction methods have attracted increasing attention. A variety of protein sequenc...

Deep Learning to Therapeutically Target Unreported Complexes.

Trends in pharmacological sciences
The disruption of large protein-protein (PP) interfaces remains a challenge in targeted therapy. Designing drugs that compete with binding partners is daunting, especially when the structure of the protein complex is unknown. To address the problem w...