scholarly journals In silico annotation of five candidate genes associated with pathogenicity in Fusarium circinatum

2018 ◽  
Vol 48 (3) ◽  
pp. e12417 ◽  
Author(s):  
E. J. Muñoz-Adalia ◽  
M. Fernández ◽  
B. D. Wingfield ◽  
J. J. Diez
Keyword(s):  
Candidate Genes ◽  
In Silico ◽  
Fusarium Circinatum

scholarly journals Expression Profiling Coupled with In-silico Mapping Identifies Candidate Genes for Reducing Aflatoxin Accumulation in Maize

2017 ◽  
Vol 8 ◽  
Author(s):  
Ramesh Dhakal ◽  
Chenglin Chai ◽  
Ratna Karan ◽  
Gary L. Windham ◽  
William P. Williams ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Expression Profiling ◽  
In Silico ◽  
In Silico Mapping ◽  
Aflatoxin Accumulation

scholarly journals Using the Phenogen website for ‘in silico’ analysis of morphine-induced analgesia: identifying candidate genes

2010 ◽  
Vol 16 (3) ◽  
pp. 393-404 ◽  
Author(s):  
Paula L. Hoffman ◽  
Beth Bennett ◽  
Laura M. Saba ◽  
Sanjiv V. Bhave ◽  
Phyllis J. Carosone-Link ◽  
...  
Keyword(s):  
Candidate Genes ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

Novel candidate genes of the PARK7 interactome as mediators of apoptosis and acetylation in multiple sclerosis: An in silico analysis

2018 ◽  
Vol 19 ◽  
pp. 8-14 ◽  
Author(s):  
George D. Vavougios ◽  
Sotirios G. Zarogiannis ◽  
Karen Angeliki Krogfelt ◽  
Konstantinos Gourgoulianis ◽  
Dimos Dimitrios Mitsikostas ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Candidate Genes ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

In silico identification of new candidate genes for hereditary congenital facial paresis

2011 ◽  
Vol 29 (4) ◽  
pp. 451-460 ◽  
Author(s):  
Laura Tomás‐Roca ◽  
Antonio Pérez‐Aytés ◽  
Luis Puelles ◽  
Faustino Marín
Keyword(s):  
Candidate Genes ◽  
In Silico ◽  
Facial Paresis ◽  
In Silico Identification

scholarly journals De novo assembly of the pepper transcriptome (Capsicum annuum): a benchmark for in silico discovery of SNPs, SSRs and candidate genes

BMC Genomics ◽  
2012 ◽  
Vol 13 (1) ◽  
pp. 571 ◽  
Author(s):  
Hamid Ashrafi ◽  
Theresa Hill ◽  
Kevin Stoffel ◽  
Alexander Kozik ◽  
JiQiang Yao ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Capsicum Annuum ◽  
De Novo Assembly ◽  
In Silico ◽  
De Novo

Analysis of candidate genes in the CLN6 critical regionusing in silico cloning

2001 ◽  
Vol 5 ◽  
pp. 29-31 ◽  
Author(s):  
Julie D. Sharp ◽  
Ruth B. Wheeler ◽  
Roger A. Schultz ◽  
John M. Joslin ◽  
Sara E. Mole ◽  
...  
Keyword(s):  
Candidate Genes ◽  
In Silico ◽  
In Silico Cloning

scholarly journals In-silico analysis of differentially expressed genes and their regulating microRNA involved in lymph node metastasis in invasive breast carcinoma

2020 ◽  
Author(s):  
Anupama Modi ◽  
Purvi Purohit ◽  
Ashita Gadwal ◽  
Shweta Ukey ◽  
Dipayan Roy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
In Silico ◽  
Nodal Metastasis ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Node Metastasis

AbstractIntroductionAxillary nodal metastasis is related to poor prognosis in breast cancer (BC). The metastatic progression in BC is related to molecular signatures. The currently popular methods to evaluate nodal status may give false negatives or give rise to secondary complications. In this study, key candidate genes in BC lymph node metastasis have been identified from publicly available microarray datasets and their roles in BC have been explored through survival analysis and target prediction.MethodsGene Expression Omnibus datasets have been analyzed for differentially expressed genes (DEGs) in lymph node-positive BC patients compared to nodal-negative and healthy tissues. The functional enrichment analysis was done in database for annotation, visualization and integrated discovery (DAVID). Protein-protein interaction (PPI) network was constructed in Search Tool for the Retrieval of Interacting Genes and proteins (STRING) and visualized on Cytoscape. The candidate hub genes were identified and their expression analyzed for overall survival (OS) in Gene Expression Profiling Interactive Analysis (GEPIA). The target miRNA and transcription factors were analyzed through miRNet.ResultsA total of 102 overlapping DEGs were found. Gene Ontology revealed eleven, seventeen, and three significant terms for cellular component, biological process, and molecular function respectively. Six candidate genes, DSC3, KRT5, KRT6B, KRT17, KRT81, and SERPINB5 were significantly associated with nodal metastasis and OS in BC patients. A total of 83 targeting miRNA were identified through miRNet and hsa-miR-155-5p was found to be the most significant miRNA which was targeting five out of six hub genes.ConclusionIn-silico survival and expression analyses revealed six candidate genes and 83 miRNAs, which may be potential diagnostic markers and therapeutic targets in BC patients and miR-155-5p shows promise as it targeted five important hub genes related to lymph-node metastasis.

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