scholarly journals Parallel Fast Dynamic Algorithm for Sequence Alignment Using OpenMP and Partitioning Scheme

2021 ◽  
Vol 8 (2) ◽  
pp. 38-43
Author(s):  
Sara shehab
2012 ◽  
Vol 37 (7) ◽  
pp. 54-61
Author(s):  
Sara A.Shehab ◽  
Arabi Keshk ◽  
Hany Mahgoub

Author(s):  
Kristopher D. Staller ◽  
Corey Goodrich

Abstract Soft Defect Localization (SDL) is a dynamic laser-based failure analysis technique that can detect circuit upsets (or cause a malfunctioning circuit to recover) by generation of localized heat or photons from a rastered laser beam. SDL is the third and seldom used method on the LSM tool. Most failure analysis LSM sessions use the endo-thermic mode (TIVA, XIVA, OBIRCH), followed by the photo-injection mode (LIVA) to isolate most of their failures. SDL is seldom used or attempted, unless there is a unique and obvious failure mode that can benefit from the application. Many failure analysts, with a creative approach to the analysis, can employ SDL. They will benefit by rapidly finding the location of the failure mechanism and forgoing weeks of nodal probing and isolation. This paper will cover circuit signal conditioning to allow for fast dynamic failure isolation using an LSM for laser stimulation. Discussions of several cases will demonstrate how the laser can be employed for triggering across a pass/fail boundary as defined by voltage levels, supply currents, signal frequency, or digital flags. A technique for manual input of the LSM trigger is also discussed.


2011 ◽  
Author(s):  
M. A. Green ◽  
C. R. Kaplan ◽  
J. P. Boris ◽  
E. S. Oran

2020 ◽  
Vol 17 (1) ◽  
pp. 59-77
Author(s):  
Anand Kumar Nelapati ◽  
JagadeeshBabu PonnanEttiyappan

Background:Hyperuricemia and gout are the conditions, which is a response of accumulation of uric acid in the blood and urine. Uric acid is the product of purine metabolic pathway in humans. Uricase is a therapeutic enzyme that can enzymatically reduces the concentration of uric acid in serum and urine into more a soluble allantoin. Uricases are widely available in several sources like bacteria, fungi, yeast, plants and animals.Objective:The present study is aimed at elucidating the structure and physiochemical properties of uricase by insilico analysis.Methods:A total number of sixty amino acid sequences of uricase belongs to different sources were obtained from NCBI and different analysis like Multiple Sequence Alignment (MSA), homology search, phylogenetic relation, motif search, domain architecture and physiochemical properties including pI, EC, Ai, Ii, and were performed.Results:Multiple sequence alignment of all the selected protein sequences has exhibited distinct difference between bacterial, fungal, plant and animal sources based on the position-specific existence of conserved amino acid residues. The maximum homology of all the selected protein sequences is between 51-388. In singular category, homology is between 16-337 for bacterial uricase, 14-339 for fungal uricase, 12-317 for plants uricase, and 37-361 for animals uricase. The phylogenetic tree constructed based on the amino acid sequences disclosed clusters indicating that uricase is from different source. The physiochemical features revealed that the uricase amino acid residues are in between 300- 338 with a molecular weight as 33-39kDa and theoretical pI ranging from 4.95-8.88. The amino acid composition results showed that valine amino acid has a high average frequency of 8.79 percentage compared to different amino acids in all analyzed species.Conclusion:In the area of bioinformatics field, this work might be informative and a stepping-stone to other researchers to get an idea about the physicochemical features, evolutionary history and structural motifs of uricase that can be widely used in biotechnological and pharmaceutical industries. Therefore, the proposed in silico analysis can be considered for protein engineering work, as well as for gout therapy.


2019 ◽  
Vol 15 (4) ◽  
pp. 353-362
Author(s):  
Sambhaji B. Thakar ◽  
Maruti J. Dhanavade ◽  
Kailas D. Sonawane

Background: Legume plants are known for their rich medicinal and nutritional values. Large amount of medicinal information of various legume plants have been dispersed in the form of text. Objective: It is essential to design and construct a legume medicinal plants database, which integrate respective classes of legumes and include knowledge regarding medicinal applications along with their protein/enzyme sequences. Methods: The design and development of Legume Medicinal Plants Database (LegumeDB) has been done by using Microsoft Structure Query Language Server 2017. DBMS was used as back end and ASP.Net was used to lay out front end operations. VB.Net was used as arranged program for coding. Multiple sequence alignment, phylogenetic analysis and homology modeling techniques were also used. Results: This database includes information of 50 Legume medicinal species, which might be helpful to explore the information for researchers. Further, maturase K (matK) protein sequences of legumes and mangroves were retrieved from NCBI for multiple sequence alignment and phylogenetic analysis to understand evolutionary lineage between legumes and mangroves. Homology modeling technique was used to determine three-dimensional structure of matK from Legume species i.e. Vigna unguiculata using matK of mangrove species, Thespesia populnea as a template. The matK sequence analysis results indicate the conserved residues among legume and mangrove species. Conclusion: Phylogenetic analysis revealed closeness between legume species Vigna unguiculata and mangrove species Thespesia populnea to each other, indicating their similarity and origin from common ancestor. Thus, these studies might be helpful to understand evolutionary relationship between legumes and mangroves. : LegumeDB availability: http://legumedatabase.co.in


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