Bioinformatics Tools for Exploring the SUMO Gene Network

2016 ◽  
pp. 285-301
Author(s):  
Pedro Humberto Castro ◽  
Miguel Ângelo Santos ◽  
Alexandre Papadopoulos Magalhães ◽  
Rui Manuel Tavares ◽  
Herlânder Azevedo
Keyword(s):  
Gene Network ◽  
Bioinformatics Tools

Reconstruction of Dementia Gene Network Using Online Bioinformatics Tools

2020 ◽  
Author(s):  
Sergey S. Kovalev ◽  
Arthur I. Dergilev ◽  
Yuriy L. Orlov ◽  
Oleg D. Fateev ◽  
Urana N. Kavai-ool
Keyword(s):  
Gene Network ◽  
Bioinformatics Tools

scholarly journals Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Natalya V. Gubanova ◽  
Nina G. Orlova ◽  
Arthur I. Dergilev ◽  
Nina Y. Oparina ◽  
Yuriy L. Orlov
Keyword(s):  
Gene Network ◽  
High Throughput Sequencing ◽  
Gene List ◽  
Underlying Disease ◽  
Network Reconstruction ◽  
Sequencing Analysis ◽  
Therapy Targets ◽  
Bioinformatics Tools ◽  
Random Arrangement ◽  
Gene Network Reconstruction

Abstract Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

Dissecting the meiotic gene network in female embryonic germ cells

2014 ◽  
Author(s):  
Emilie Abby ◽  
Sophie Tourpin ◽  
Marie-Justine Guerquin ◽  
Bouffant Ronan Le ◽  
Rene Habert ◽  
...  
Keyword(s):  
Germ Cells ◽  
Gene Network ◽  
Embryonic Germ Cells ◽  
Meiotic Gene

Tbx1 and Fgf11 Are Alongside Sox6 and Sox9 Part of a Gene Network That Regulates Forelimb Development

2019 ◽  
Author(s):  
Gautier Tejedor ◽  
Béryl Laplace-Builhé ◽  
Patricia Luz-Crawford ◽  
Said Assou ◽  
Audrey Barthelaix ◽  
...  
Keyword(s):  
Gene Network

Integrating Bioinformatics Strategies in Cancer Immunotherapy: Current and Future Perspectives

2020 ◽  
Vol 23 (8) ◽  
pp. 687-698 ◽  
Author(s):  
Houda N. Washah ◽  
Elliasu Y. Salifu ◽  
Opeyemi Soremekun ◽  
Ahmed A. Elrashedy ◽  
Geraldene Munsamy ◽  
...  
Keyword(s):  
Cancer Immunotherapy ◽  
Therapeutic Potential ◽  
Cell Cancer ◽  
Full Potential ◽  
Future Perspectives ◽  
The Past ◽  
Bioinformatics Tools ◽  
Treatment Paradigm ◽  
Immunotherapy Of Cancer ◽  
Significant Attention

For the past few decades, the mechanisms of immune responses to cancer have been exploited extensively and significant attention has been given into utilizing the therapeutic potential of the immune system. Cancer immunotherapy has been established as a promising innovative treatment for many forms of cancer. Immunotherapy has gained its prominence through various strategies, including cancer vaccines, monoclonal antibodies (mAbs), adoptive T cell cancer therapy, and immune checkpoint therapy. However, the full potential of cancer immunotherapy is yet to be attained. Recent studies have identified the use of bioinformatics tools as a viable option to help transform the treatment paradigm of several tumors by providing a therapeutically efficient method of cataloging, predicting and selecting immunotherapeutic targets, which are known bottlenecks in the application of immunotherapy. Herein, we gave an insightful overview of the types of immunotherapy techniques used currently, their mechanisms of action, and discussed some bioinformatics tools and databases applied in the immunotherapy of cancer. This review also provides some future perspectives in the use of bioinformatics tools for immunotherapy.

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