In silico prediction of physical protein interactions and characterization of interactome orphans

2014 ◽  
Vol 12 (1) ◽  
pp. 79-84 ◽  
Author(s):  
Max Kotlyar ◽  
Chiara Pastrello ◽  
Flavia Pivetta ◽  
Alessandra Lo Sardo ◽  
Christian Cumbaa ◽  
...  
Keyword(s):  
Protein Interactions ◽  
In Silico ◽  
In Silico Prediction

scholarly journals In Silico Prediction and Functional Characterization of Genes Related to Abiotic and Biotic Stresses in Chickpea (Cicer arietinum)

2018 ◽  
Vol 7 (1) ◽  
pp. 1-35
Author(s):  
Sukhdeep Kaur ◽  
Satendra Singh ◽  
Gitanjali Tandon ◽  
Sarika Jaiswal ◽  
Mir Asif Iquebal ◽  
...  
Keyword(s):  
Cicer Arietinum ◽  
In Silico ◽  
Functional Characterization ◽  
In Silico Prediction ◽  
Abiotic And Biotic Stresses ◽  
Biotic Stresses

scholarly journals Molecular Characterization of Hepatitis C Virus for Developed Antiviral Agents Resistance Mutations and New Insights into in-silico Prediction Studies

2020 ◽  
Vol Volume 13 ◽  
pp. 4235-4248
Author(s):  
Mohamed M Adel El-Sokkary ◽  
Lizaveta Gotina ◽  
Mohammad M. Al-Sanea ◽  
Ae Nim Pae ◽  
Rehab Mohammed Elbargisy
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Molecular Characterization ◽  
In Silico ◽  
Antiviral Agents ◽  
In Silico Prediction ◽  
Resistance Mutations

In Silico Prediction and Characterization of MicroRNAs From Aphis gossypii (Hemiptera: Aphididae)

2014 ◽  
Vol 107 (2) ◽  
pp. 521-531 ◽  
Author(s):  
K. B. Rebijith ◽  
R. Asokan ◽  
V. Krishna ◽  
Ranjitha H. Hande ◽  
N. K. Krishna Kumar ◽  
...  
Keyword(s):  
In Silico ◽  
Aphis Gossypii ◽  
In Silico Prediction

Improved detection of motifs with preferential location in promoters

Genome ◽  
2010 ◽  
Vol 53 (9) ◽  
pp. 739-752 ◽  
Author(s):  
Virginie Bernard ◽  
Alain Lecharny ◽  
Véronique Brunaud
Keyword(s):  
In Silico ◽  
Gene Expression Regulation ◽  
Window Size ◽  
Sliding Window ◽  
In Silico Prediction ◽  
Distribution Profile ◽  
Topological Constraints ◽  
Automatic Adaptation ◽  
Preferential Location

Many transcription factor binding sites (TFBSs) involved in gene expression regulation are preferentially located relative to the transcription start site. This property is exploited in in silico prediction approaches, one of which involves studying the local overrepresentation of motifs using a sliding window to scan promoters with considerable accuracy. Nevertheless, the consequences of the choice of the sliding window size have never before been analysed. We propose an automatic adaptation of this size to each motif distribution profile. This approach allows a better characterization of the topological constraints of the motifs and the lists of genes containing them. Moreover, our approach allowed us to highlight a nonconstant frequency of occurrence of spurious motifs that could be counter-selected close to their functional area. Therefore, to improve the accuracy of in silico prediction of TFBSs and the sensitivity of the promoter cartography, we propose, in addition to automatic adaptation of window size, consideration of the nonconstant frequency of motifs in promoters.

scholarly journals In silico prediction of protein-protein interactions in human macrophages

2014 ◽  
Vol 7 (1) ◽  
pp. 157 ◽  
Author(s):  
Oussema Souiai ◽  
Fatma Guerfali ◽  
Slimane Ben Miled ◽  
Christine Brun ◽  
Alia Benkahla
Keyword(s):  
Protein Interactions ◽  
In Silico ◽  
In Silico Prediction ◽  
Protein Protein Interactions ◽  
Human Macrophages

scholarly journals Research paper In silico prediction and characterization of three-dimensional structure of Actin-1 of Arabidopsis thaliana

2013 ◽  
Vol 4 ◽  
pp. 432-443
Author(s):  
Mousumi Sahu ◽  
Budheswar Dehury ◽  
Ranjan Sarmah ◽  
Smita Sahoo ◽  
Jagajjit Sahu ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
In Silico ◽  
Three Dimensional ◽  
Research Paper ◽  
Dimensional Structure ◽  
In Silico Prediction ◽  
Three Dimensional Structure

Genomic and in silico Structural Characterization of Dobrava-Belgrade orthohantavirus Isolate from European Side of Turkey

2021 ◽  
Author(s):  
Mert Erdin ◽  
Ceylan Polat ◽  
Teemu Smura ◽  
Sercan Irmak ◽  
Ortac Cetintas ◽  
...  
Keyword(s):  
Amino Acid ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Viral Protein ◽  
In Silico ◽  
Protein Structures ◽  
Whole Genome ◽  
In Silico Prediction ◽  
The Balkans

Abstract Orthohantaviruses are transmitted to humans mostly through small mammals that are the reservoirs of these viruses. Because orthohantaviruses show high genetic variability through geographic regions, the genetic characterization of these viruses with whole genome sequencing is of great importance to clarify the molecular epidemiology and track their genetic changes in the reservoir hosts. We have previously reported the presence of Dobrava-Belgrade orthohantavirus (DOBV) in the Igneada region, Kirklareli province by showing antibodies against the virus in rodents and by sequencing partial genomes of the virus. Here we report the whole genome sequencing of DOBV Igneada strain directly from Apodemus flavicollis’ lung tissue by next-generation sequencing followed by phylogenetic analyses. In addition, viral protein structures of DOBV Igneada strain were modelled, and in silico prediction analyses of amino acid changes on viral protein function and stability were performed.The phylogenetic analysis showed a close relation between the DOBV Igneada strain from Turkey and DOBV Ano-Poroia strain from Greece. Similarity plot analysis revealed also similarities between DOBV Igneada strain and other DOBV strains from the Balkans such as Greece, Croatia, and Slovenia. Additionally, in silico prediction suggested that G318E, Y322H, and S324P mutations on Gn glycoprotein are deleterious, and all amino acid changes decrease the stability of both Gn and Gc glycoproteins.In conclusion, full orthohantaviral genomes can be obtained directly from rodent lung tissues allowing detailed genetic and structural analyses of orthohantaviruses. The DOBV Igneada strain shows great similarity to the prototype Ano-Poroia strain, yet it was predicted that DOBV Igneada strain may have some changes on its pathogenicity and its structure warranting further research.

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