Comparison of sequence and structure-based datasets for nonredundant structural data mining

2005 ◽  
Vol 60 (4) ◽  
pp. 577-583 ◽  
Author(s):  
Carmen K. Chu ◽  
Lina L. Feng ◽  
Merridee A. Wouters
Keyword(s):  
Author(s):  
Markella Konstantinidou ◽  
Zlata Boiarska ◽  
Roberto Butera ◽  
Constantinos G. Neochoritis ◽  
Katarzyna Kurpiewska ◽  
...  
Keyword(s):  

2016 ◽  
Vol 38 ◽  
pp. 53-61 ◽  
Author(s):  
Briallen Lobb ◽  
Andrew C Doxey

Author(s):  
Courtney Corley ◽  
Diane Cook ◽  
Armin Mikler ◽  
Karan Singh

Author(s):  
Meenu Gupta ◽  
Vijender Kumar Solanki ◽  
Vijay Kumar Singh ◽  
Vicente García-Díaz

Data mining is used in various domains of research to identify a new cause for tan effect in the society over the globe. This article includes the same reason for using the data mining to identify the Accident Occurrences in different regions and to identify the most valid reason for happening accidents over the globe. Data Mining and Advanced Machine Learning algorithms are used in this research approach and this article discusses about hyperline, classifications, pre-processing of the data, training the machine with the sample datasets which are collected from different regions in which we have structural and semi-structural data. We will dive into deep of machine learning and data mining classification algorithms to find or predict something novel about the accident occurrences over the globe. We majorly concentrate on two classification algorithms to minify the research and task and they are very basic and important classification algorithms. SVM (Support vector machine), CNB Classifier. This discussion will be quite interesting with WEKA tool for CNB classifier, Bag of Words Identification, Word Count and Frequency Calculation.


2019 ◽  
Vol 35 (24) ◽  
pp. 5334-5336 ◽  
Author(s):  
Diego Gallego ◽  
Leonardo Darré ◽  
Pablo D Dans ◽  
Modesto Orozco

Abstract Summary veriNA3d is an R package for the analysis of nucleic acids structural data, with an emphasis in complex RNA structures. In addition to single-structure analyses, veriNA3d also implements functions to handle whole datasets of mmCIF/PDB structures that could be retrieved from public/local repositories. Our package aims to fill a gap in the data mining of nucleic acids structures to produce flexible and high throughput analysis of structural databases. Availability and implementation http://mmb.irbbarcelona.org/gitlab/dgallego/veriNA3d. Supplementary information Supplementary data are available at Bioinformatics online.


2005 ◽  
Vol 4 (2) ◽  
pp. 33-42
Author(s):  
Hiroaki KATO ◽  
Shin-ichi CHIKAMATSU ◽  
Yoshimasa TAKAHASHI ◽  
Hidetsugu ABE

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