Literature DB >> 25450261

Contribution of bioinformatics prediction in microRNA-based cancer therapeutics.

Jasjit K Banwait1, Dhundy R Bastola2.   

Abstract

Despite enormous efforts, cancer remains one of the most lethal diseases in the world. With the advancement of high throughput technologies massive amounts of cancer data can be accessed and analyzed. Bioinformatics provides a platform to assist biologists in developing minimally invasive biomarkers to detect cancer, and in designing effective personalized therapies to treat cancer patients. Still, the early diagnosis, prognosis, and treatment of cancer are an open challenge for the research community. MicroRNAs (miRNAs) are small non-coding RNAs that serve to regulate gene expression. The discovery of deregulated miRNAs in cancer cells and tissues has led many to investigate the use of miRNAs as potential biomarkers for early detection, and as a therapeutic agent to treat cancer. Here we describe advancements in computational approaches to predict miRNAs and their targets, and discuss the role of bioinformatics in studying miRNAs in the context of human cancer. Published by Elsevier B.V.

Entities:  

Keywords:  Bioinformatics; Computational model; MiRNAs; MicroRNAs; Pancreatic cancer; Therapy

Mesh:

Substances:

Year:  2014        PMID: 25450261      PMCID: PMC4277182          DOI: 10.1016/j.addr.2014.10.030

Source DB:  PubMed          Journal:  Adv Drug Deliv Rev        ISSN: 0169-409X            Impact factor:   15.470


  107 in total

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Journal:  Cell       Date:  2005-03-11       Impact factor: 41.582

4.  Molecular classification of cutaneous malignant melanoma by gene expression profiling.

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8.  Mathematical and statistical modeling in cancer systems biology.

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Authors:  Clarissa P C Gomes; Ji-Hoon Cho; Leroy Hood; Octávio L Franco; Rinaldo W Pereira; Kai Wang
Journal:  Front Genet       Date:  2013-05-15       Impact factor: 4.599

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2.  Network-based identification of microRNAs as potential pharmacogenomic biomarkers for anticancer drugs.

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4.  Aberrant expression of a five-microRNA signature in breast carcinoma as a promising biomarker for diagnosis.

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5.  Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data.

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6.  Plasma Levels of miR-27a, miR-130b, and miR-301a in Polycystic Ovary Syndrome.

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7.  miR-16-5p Promotes Erythroid Maturation of Erythroleukemia Cells by Regulating Ribosome Biogenesis.

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Review 8.  Determining The Role of MicroRNAs in Self-Renewal, Metastasis and Resistance to Drugs in Human Gastric Cancer Based on Data Mining Approaches: A Systematic Review.

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9.  Significance of STAT3 in Immune Infiltration and Drug Response in Cancer.

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Review 10.  The Anti-Cancer Mechanisms of Berberine: A Review.

Authors:  Ye Wang; Yanfang Liu; Xinyang Du; Hong Ma; Jing Yao
Journal:  Cancer Manag Res       Date:  2020-01-30       Impact factor: 3.989

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