Bioinformatics Tools for Predicting GPCR Gene Functions

2013 ◽  
pp. 205-224 ◽  
Author(s):  
Makiko Suwa
Keyword(s):  
Bioinformatics Tools ◽  
Gene Functions ◽  
Gpcr Gene

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.

scholarly journals Rare Variants Imputation in Admixed Populations: Comparison Across Reference Panels and Bioinformatics Tools

2019 ◽  
Vol 10 ◽  
Author(s):  
Sanjeev Sariya ◽  
Joseph H. Lee ◽  
Richard Mayeux ◽  
Badri N. Vardarajan ◽  
Dolly Reyes-Dumeyer ◽  
...  
Keyword(s):  
Rare Variants ◽  
Bioinformatics Tools

scholarly journals Whole-Genome Sequencing for Investigating a Health Care-Associated Outbreak of Carbapenem-Resistant Acinetobacter baumannii

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 201
Author(s):  
Sang Mee Hwang ◽  
Hee Won Cho ◽  
Tae Yeul Kim ◽  
Jeong Su Park ◽  
Jongtak Jung ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Acinetobacter Baumannii ◽  
Genome Sequencing ◽  
Snp Analysis ◽  
Whole Genome ◽  
Phylogenetic Tree Analysis ◽  
Web Based ◽  
Hospital Outbreak ◽  
Carbapenem Resistant ◽  
Bioinformatics Tools

Carbapenem-resistant Acinetobacter baumannii (CRAB) outbreaks in hospital settings challenge the treatment of patients and infection control. Understanding the relatedness of clinical isolates is important in distinguishing outbreak isolates from sporadic cases. This study investigated 11 CRAB isolates from a hospital outbreak by whole-genome sequencing (WGS), utilizing various bioinformatics tools for outbreak analysis. The results of multilocus sequence typing (MLST), single nucleotide polymorphism (SNP) analysis, and phylogenetic tree analysis by WGS through web-based tools were compared, and repetitive element polymerase chain reaction (rep-PCR) typing was performed. Through the WGS of 11 A. baumannii isolates, three clonal lineages were identified from the outbreak. The coexistence of blaOXA-23, blaOXA-66, blaADC-25, and armA with additional aminoglycoside-inactivating enzymes, predicted to confer multidrug resistance, was identified in all isolates. The MLST Oxford scheme identified three types (ST191, ST369, and ST451), and, through whole-genome MLST and whole-genome SNP analyses, different clones were found to exist within the MLST types. wgSNP showed the highest discriminatory power with the lowest similarities among the isolates. Using the various bioinformatics tools for WGS, CRAB outbreak analysis was applicable and identified three discrete clusters differentiating the separate epidemiologic relationships among the isolates.

scholarly journals Epigenetic dysregulation of immune-related pathways in cancer: bioinformatics tools and visualization

2021 ◽  
Author(s):  
Anders Berglund ◽  
Ryan M. Putney ◽  
Imene Hamaidi ◽  
Sungjune Kim
Keyword(s):  
Patient Outcome ◽  
Immune Responses ◽  
Cancer Cells ◽  
Immune Evasion ◽  
Epigenetic Regulation ◽  
Current Evidence ◽  
Immune Recognition ◽  
Bioinformatics Tools ◽  
Visualization Techniques ◽  
Cancer Bioinformatics

AbstractCancer immune evasion is one of the hallmarks of carcinogenesis. Cancer cells employ multiple mechanisms to avoid immune recognition and suppress antitumor immune responses. Recently, accumulating evidence has indicated that immune-related pathways are epigenetically dysregulated in cancer. Most importantly, the epigenetic footprint of immune-related pathways is associated with the patient outcome, underscoring the crucial need to understand this process. In this review, we summarize the current evidence for epigenetic regulation of immune-related pathways in cancer and describe bioinformatics tools, informative visualization techniques, and resources to help decipher the cancer epigenome.

scholarly journals Genome-wide interrogation of gene functions through base editor screens empowered by barcoded sgRNAs

2021 ◽  
Author(s):  
Ping Xu ◽  
Zhiheng Liu ◽  
Ying Liu ◽  
Huazheng Ma ◽  
Yiyuan Xu ◽  
...  
Keyword(s):  
Genome Wide ◽  
Gene Functions

scholarly journals Use of an Alignment-Free Method for the Geographical Discrimination of GTPVs Based on the GPCR Sequences

2021 ◽  
Vol 9 (4) ◽  
pp. 855
Author(s):  
Tesfaye Rufael Chibssa ◽  
Yang Liu ◽  
Melaku Sombo ◽  
Jacqueline Kasiiti Lichoti ◽  
Janchivdorj Erdenebaatar ◽  
...  
Keyword(s):  
Lumpy Skin Disease ◽  
Alignment Free ◽  
Central Asian ◽  
Source Tracing ◽  
Geographical Regions ◽  
Gpcr Gene ◽  
Geographical Discrimination ◽  
Sequence Profiles ◽  
G Protein Coupled ◽  
Effective Source

Goatpox virus (GTPV) belongs to the genus Capripoxvirus, together with sheeppox virus (SPPV) and lumpy skin disease virus (LSDV). GTPV primarily affects sheep, goats and some wild ruminants. Although GTPV is only present in Africa and Asia, the recent spread of LSDV in Europe and Asia shows capripoxviruses could escape their traditional geographical regions to cause severe outbreaks in new areas. Therefore, it is crucial to develop effective source tracing of capripoxvirus infections. Earlier, conventional phylogenetic methods, based on limited samples, identified three different nucleotide sequence profiles in the G-protein-coupled chemokine receptor (GPCR) gene of GTPVs. However, this method did not differentiate GTPV strains by their geographical origins. We have sequenced the GPCR gene of additional GTPVs and analyzed them with publicly available sequences, using conventional alignment-based methods and an alignment-free approach exploiting k-mer frequencies. Using the alignment-free method, we can now classify GTPVs based on their geographical origin: African GTPVs and Asian GTPVs, which further split into Western and Central Asian (WCA) GTPVs and Eastern and Southern Asian (ESA) GTPVs. This approach will help determine the source of introduction in GTPV emergence in disease-free regions and detect the importation of additional strains in disease-endemic areas.

Sign in / Sign up

Export Citation Format

Share Document