Literature DB >> 15364067

Bioinformatics and cancer target discovery.

Brian Desany1, Zemin Zhang.   

Abstract

The convergence of genomic technologies and the development of drugs designed against specific molecular targets provides many opportunities for using bioinformatics to bridge the gap between biological knowledge and clinical therapy. Identifying genes that have properties similar to known targets is conceptually straightforward. Additionally, genes can be linked to cancer via recurrent genomic or genetic abnormalities. Finally, by integrating large and disparate datasets, gene-level distinctions can be made between the different biological states that the data represents. These bioinformatics approaches and their associated methodologies, which can be applied across a range of technologies, facilitate the rapid identification of new target leads for further experimental validation.

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Year:  2004        PMID: 15364067     DOI: 10.1016/S1359-6446(04)03224-6

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  7 in total

1.  In-silico prediction of drug targets, biological activities, signal pathways and regulating networks of dioscin based on bioinformatics.

Authors:  Lianhong Yin; Lingli Zheng; Lina Xu; Deshi Dong; Xu Han; Yan Qi; Yanyan Zhao; Youwei Xu; Jinyong Peng
Journal:  BMC Complement Altern Med       Date:  2015-03-05       Impact factor: 3.659

2.  GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses.

Authors:  Zefang Tang; Chenwei Li; Boxi Kang; Ge Gao; Cheng Li; Zemin Zhang
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

3.  Large-scale in-silico identification of a tumor-specific antigen pool for targeted immunotherapy in triple-negative breast cancer.

Authors:  Jessica Kaufmann; Nicolas Wentzensen; Titus J Brinker; Niels Grabe
Journal:  Oncotarget       Date:  2019-04-02

4.  The cuproptosis-related signature associated with the tumor environment and prognosis of patients with glioma.

Authors:  Weichen Wang; Zhichao Lu; Maoyu Wang; Zongheng Liu; Bing Wu; Chengkai Yang; He Huan; Peipei Gong
Journal:  Front Immunol       Date:  2022-08-30       Impact factor: 8.786

5.  Identifying new targets in leukemogenesis using computational approaches.

Authors:  Archana Jayaraman; Kaiser Jamil; Haseeb A Khan
Journal:  Saudi J Biol Sci       Date:  2015-01-20       Impact factor: 4.219

6.  Computational selection of antibody-drug conjugate targets for breast cancer.

Authors:  François Fauteux; Jennifer J Hill; Maria L Jaramillo; Youlian Pan; Sieu Phan; Fazel Famili; Maureen O'Connor-McCourt
Journal:  Oncotarget       Date:  2016-01-19

7.  Autophagy-related circRNA evaluation reveals hsa_circ_0001747 as a potential favorable prognostic factor for biochemical recurrence in patients with prostate cancer.

Authors:  Chuanfan Zhong; Kaihui Wu; Shuo Wang; Zining Long; Taowei Yang; Weibo Zhong; Xiao Tan; Zixian Wang; Chuanyin Li; Jianming Lu; Xiangming Mao
Journal:  Cell Death Dis       Date:  2021-07-22       Impact factor: 8.469

  7 in total

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