Data mining, neural nets, trees — Problems 2 and 3 of Genetic Analysis Workshop 15

2007 ◽  
Vol 31 (S1) ◽  
pp. S51-S60 ◽  
Author(s):  
Andreas Ziegler ◽  
Anita L. DeStefano ◽  
Inke R. König ◽  
Keyword(s):  
Data Mining ◽  
Genetic Analysis ◽  
Genetic Analysis Workshop ◽  
Neural Nets

scholarly journals Machine learning and data mining in complex genomic data—a review on the lessons learned in Genetic Analysis Workshop 19

BMC Genetics ◽  
2016 ◽  
Vol 17 (S2) ◽  
Author(s):  
Inke R. König ◽  
Jonathan Auerbach ◽  
Damian Gola ◽  
Elizabeth Held ◽  
Emily R. Holzinger ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Genetic Analysis ◽  
Genetic Analysis Workshop ◽  
Genomic Data ◽  
Lessons Learned

Data mining of RNA expression and DNA genotype data: Presentation Group 5 contributions to Genetic Analysis Workshop 15

2007 ◽  
Vol 31 (S1) ◽  
pp. S43-S50
Author(s):  
Catherine T. Falk ◽  
Stephen J. Finch ◽  
Wonkuk Kim ◽  
Nitai D. Mukhopadhyay ◽  
Keyword(s):  
Data Mining ◽  
Genetic Analysis ◽  
Genetic Analysis Workshop ◽  
Rna Expression ◽  
Genotype Data ◽  
Data Presentation ◽  
Group 5 ◽  
Presentation Group

scholarly journals Regression and data mining methods for analyses of multiple rare variants in the Genetic Analysis Workshop 17 mini-exome data

2011 ◽  
Vol 35 (S1) ◽  
pp. S92-S100 ◽  
Author(s):  
Joan E. Bailey-Wilson ◽  
Jennifer S. Brennan ◽  
Shelley B. Bull ◽  
Robert Culverhouse ◽  
Yoonhee Kim ◽  
...  
Keyword(s):  
Data Mining ◽  
Genetic Analysis ◽  
Genetic Analysis Workshop ◽  
Rare Variants ◽  
Exome Data ◽  
Mining Methods

Advanced Statistical Tools for Improving Yield and Reliability

1999 ◽  
Author(s):  
Richard C. Kittler
Keyword(s):  
Data Mining ◽  
Analysis Data ◽  
Neural Nets ◽  
Future Trends ◽  
Statistical Tools ◽  
Mining Technology ◽  
Explanatory Variables ◽  
Data Coverage ◽  
Statistical Approaches ◽  
Adequate Data

Abstract Analysis of manufacturing data as a tool for failure analysts often meets with roadblocks due to the complex non-linear behaviors of the relationships between failure rates and explanatory variables drawn from process history. The current work describes how the use of a comprehensive engineering database and data mining technology over-comes some of these difficulties and enables new classes of problems to be solved. The characteristics of the database design necessary for adequate data coverage and unit traceability are discussed. Data mining technology is explained and contrasted with traditional statistical approaches as well as those of expert systems, neural nets, and signature analysis. Data mining is applied to a number of common problem scenarios. Finally, future trends in data mining technology relevant to failure analysis are discussed.

Genetic analysis workshop III: Sampling considerations and assumptions in gene mapping

1985 ◽  
Vol 2 (2) ◽  
pp. 219-220
Author(s):  
R. Arlen Price ◽  
Patricia L. Kramer ◽  
Andrew J. Pakstis ◽  
Kenneth K. Kidd
Keyword(s):  
Genetic Analysis ◽  
Gene Mapping ◽  
Genetic Analysis Workshop

scholarly journals Simulation of a medication and methylation effects on triglycerides in the Genetic Analysis Workshop 20

2018 ◽  
Vol 12 (S9) ◽  
Author(s):  
Aldi T. Kraja ◽  
Ping An ◽  
Petra Lenzini ◽  
Shiou J. Lin ◽  
Christine Williams ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Genetic Analysis Workshop
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