Literature DB >> 16227414

Using bioinformatics and genome analysis for new therapeutic interventions.

David W Mount1, Ritu Pandey.   

Abstract

The genome era provides two sources of knowledge to investigators whose goal is to discover new cancer therapies: first, information on the 20,000 to 40,000 genes that comprise the human genome, the proteins they encode, and the variation in these genes and proteins in human populations that place individuals at risk or that occur in disease; second, genome-wide analysis of cancer cells and tissues leads to the identification of new drug targets and the design of new therapeutic interventions. Using genome resources requires the storage and analysis of large amounts of diverse information on genetic variation, gene and protein functions, and interactions in regulatory processes and biochemical pathways. Cancer bioinformatics deals with organizing and analyzing the data so that important trends and patterns can be identified. Specific gene and protein targets on which cancer cells depend can be identified. Therapeutic agents directed against these targets can then be developed and evaluated. Finally, molecular and genetic variation within a population may become the basis of individualized treatment.

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Year:  2005        PMID: 16227414     DOI: 10.1158/1535-7163.MCT-05-0150

Source DB:  PubMed          Journal:  Mol Cancer Ther        ISSN: 1535-7163            Impact factor:   6.261


  4 in total

1.  Host-microbial interactions and regulation of intestinal epithelial barrier function: From physiology to pathology.

Authors:  Linda Chia-Hui Yu; Jin-Town Wang; Shu-Chen Wei; Yen-Hsuan Ni
Journal:  World J Gastrointest Pathophysiol       Date:  2012-02-15

2.  KRAS AND THE REALITY OF PERSONALIZED MEDICINE IN NON-SMALL CELL LUNG CANCER.

Authors:  Havva O Kilgoz; Guzide Bender; Joseph M Scandura; Agnes Viale; Bahar Taneri
Journal:  Mol Med       Date:  2016-07-07       Impact factor: 6.354

3.  Cinnamaldehyde and eugenol change the expression folds of AKT1 and DKC1 genes and decrease the telomere length of human adipose-derived stem cells (hASCs): An experimental and in silico study.

Authors:  Abdorrahim Absalan; Seyed Alireza Mesbah-Namin; Taki Tiraihi; Taher Taheri
Journal:  Iran J Basic Med Sci       Date:  2017-03       Impact factor: 2.699

4.  Genetic variations analysis for complex brain disease diagnosis using machine learning techniques: opportunities and hurdles.

Authors:  Hala Ahmed; Louai Alarabi; Shaker El-Sappagh; Hassan Soliman; Mohammed Elmogy
Journal:  PeerJ Comput Sci       Date:  2021-09-20
  4 in total

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