scholarly journals Prefix Tree Indexing for Similarity Search and Similarity Joins on Genomic Data

2010 ◽  
pp. 519-536 ◽  
Author(s):  
Astrid Rheinländer ◽  
Martin Knobloch ◽  
Nicky Hochmuth ◽  
Ulf Leser
Keyword(s):  
Similarity Search ◽  
Genomic Data ◽  
Prefix Tree ◽  
Similarity Joins

Efficient Metric Indexing for Similarity Search and Similarity Joins

2017 ◽  
Vol 29 (3) ◽  
pp. 556-571 ◽  
Author(s):  
Lu Chen ◽  
Yunjun Gao ◽  
Xinhan Li ◽  
Christian S. Jensen ◽  
Gang Chen
Keyword(s):  
Similarity Search ◽  
Similarity Joins

Phylogeny of actin and tubulin gene homologs in diverse eukaryotic species

2019 ◽  
Vol 79 (01S) ◽  
Author(s):  
Pawan Kumar Jayaswal ◽  
Asheesh Shanker ◽  
Nagendra Kumar Singh
Keyword(s):  
Evolutionary Relationship ◽  
Genomic Data ◽  
Gene Clusters ◽  
Species Trees ◽  
Model Species ◽  
Tubulin Gene ◽  
Tubulin Genes ◽  
Eukaryotic Species ◽  
Relationship Of ◽  
Insight Into

Actin and tubulin are cytoskeleton proteins, which are important components of the celland are conserved across species. Despite their crucial significance in cell motility and cell division the distribution and phylogeny of actin and tubulin genes across taxa is poorly understood. Here we used publicly available genomic data of 49 model species of plants, animals, fungi and Protista for further understanding the distribution of these genes among diverse eukaryotic species using rice as reference. The highest numbers of rice actin and tubulin gene homologs were present in plants followed by animals, fungi and Protista species, whereas ten actin and nine tubulin genes were conserved in all 49 species. Phylogenetic analysis of 19 actin and 18 tubulin genes clustered them into four major groups each. One each of the actin and tubulin gene clusters was conserved across eukaryotic species. Species trees based on the conserved actin and tubulin genes showed evolutionary relationship of 49 different taxa clustered into plants, animals, fungi and Protista. This study provides a phylogenetic insight into the evolution of actin and tubulin genes in diverse eukaryotic species.

Similarity Search in Data Stream with Adaptive Segmental Approximations

2009 ◽  
Vol 20 (10) ◽  
pp. 2867-2884 ◽  
Author(s):  
Feng WU ◽  
Yan ZHONG ◽  
Quan-Yuan WU ◽  
Yan JIA ◽  
Shu-Qiang YANG
Keyword(s):  
Similarity Search ◽  
Data Stream

PPR based similarity search for gas monitoring data

2009 ◽  
Vol 28 (10) ◽  
pp. 2721-2721 ◽  
Author(s):  
Ai-guo LI ◽  
Hua ZHAO
Keyword(s):  
Similarity Search ◽  
Monitoring Data ◽  
Gas Monitoring

Combined QSAR Model and Chemical Similarity Search for Novel HMG-CoA Reductase Inhibitors for Coronary Heart Disease

2020 ◽  
Vol 16 (4) ◽  
pp. 473-485
Author(s):  
David Mary Rajathei ◽  
Subbiah Parthasarathy ◽  
Samuel Selvaraj
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Similarity Search ◽  
Qsar Model ◽  
Chemical Similarity ◽  
Cholesterol Accumulation ◽  
Reductase Inhibitors ◽  
Pubchem Database ◽  
Hmg Coa Reductase Inhibitors ◽  
Coa Reductase

Background: Coronary heart disease generally occurs due to cholesterol accumulation in the walls of the heart arteries. Statins are the most widely used drugs which work by inhibiting the active site of 3-Hydroxy-3-methylglutaryl-CoA reductase (HMGCR) enzyme that is responsible for cholesterol synthesis. A series of atorvastatin analogs with HMGCR inhibition activity have been synthesized experimentally which would be expensive and time-consuming. Methods: In the present study, we employed both the QSAR model and chemical similarity search for identifying novel HMGCR inhibitors for heart-related diseases. To implement this, a 2D QSAR model was developed by correlating the structural properties to their biological activity of a series of atorvastatin analogs reported as HMGCR inhibitors. Then, the chemical similarity search of atorvastatin analogs was performed by using PubChem database search. Results and Discussion: The three-descriptor model of charge (GATS1p), connectivity (SCH-7) and distance (VE1_D) of the molecules is obtained for HMGCR inhibition with the statistical values of R2= 0.67, RMSEtr= 0.33, R2 ext= 0.64 and CCCext= 0.76. The 109 novel compounds were obtained by chemical similarity search and the inhibition activities of the compounds were predicted using QSAR model, which were close in the range of experimentally observed threshold. Conclusion: The present study suggests that the QSAR model and chemical similarity search could be used in combination for identification of novel compounds with activity by in silico with less computation and effort.

scholarly journals Population genomic data in spider mites point to a role for local adaptation in shaping range shifts

2020 ◽  
Vol 13 (10) ◽  
pp. 2821-2835
Author(s):  
Lei Chen ◽  
Jing‐Tao Sun ◽  
Peng‐Yu Jin ◽  
Ary A. Hoffmann ◽  
Xiao‐Li Bing ◽  
...  
Keyword(s):  
Local Adaptation ◽  
Genomic Data ◽  
Spider Mites ◽  
Range Shifts ◽  
Population Genomic
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