A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer-Reference-Cited by-同舟云学术

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer

Published:2015 Issue:12 Volume:11 Page:3362-3377
ISSN:1742-206X
Container-title:Molecular BioSystems
language:en
Short-container-title:Mol. BioSyst.

Author:

Randhawa Vinay¹²³⁴⁵,Kumar Singh Anil²³⁴⁵⁶,Acharya Vishal¹²³⁴⁵

Affiliation:

1. Functional Genomics and Complex Systems Laboratory

2. Biotechnology Division

3. CSIR-Institute of Himalayan Bioresource Technology

4. Council of Scientific and Industrial Research

5. Palampur

6. India

Abstract

Network-based and cheminformatics approaches identify novel lead molecules forCXCR4, a key gene prioritized in oral cancer.

Publisher

Royal Society of Chemistry (RSC)

Subject

Molecular Biology,Biotechnology

Link

http://pubs.rsc.org/en/content/articlepdf/2015/MB/C5MB00468C

Reference201 articles.

1. Optimizing Biomarkers and Endpoints in Oral Cancer Chemoprevention Trials

2. Inhibition of oral cancer cell growth by adenovirusMnSOD plus BCNU treatment

3. Thymoquinone Induces Apoptosis in Oral Cancer Cells Through P38β Inhibition

4. An Overview of Lung Cancer Genomics and Proteomics

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