Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV)
Machine learning methods and conventions are increasingly employed for the analysis of large, complex biomedical data sets, including genome-wide association studies (GWAS). Reproducibility of machine learning... (Source: BioData Mining)
Source: BioData Mining - April 19, 2018 Category: Bioinformatics Authors: Elizabeth R. Piette and Jason H. Moore Tags: Methodology Source Type: research
Pairwise gene GO-based measures for biclustering of high-dimensional expression data
Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be use... (Source: BioData Mining)
Source: BioData Mining - March 27, 2018 Category: Bioinformatics Authors: Juan A. Nepomuceno, Alicia Troncoso, Isabel A. Nepomuceno-Chamorro and Jes ús S. Aguilar-Ruiz Tags: Research Source Type: research
A novel joint analysis framework improves identification of differentially expressed genes in cross disease transcriptomic analysis
Detecting differentially expressed (DE) genes between disease and normal control group is one of the most common analyses in genome-wide transcriptomic data. Since most studies don ’t have a lot of samples, res... (Source: BioData Mining)
Source: BioData Mining - February 20, 2018 Category: Bioinformatics Authors: Wenyi Qin and Hui Lu Tags: Methodology Source Type: research
Investigating the parameter space of evolutionary algorithms
Evolutionary computation (EC) has been widely applied to biological and biomedical data. The practice of EC involves the tuning of many parameters, such as population size, generation count, selection size, an... (Source: BioData Mining)
Source: BioData Mining - February 17, 2018 Category: Bioinformatics Authors: Moshe Sipper, Weixuan Fu, Karuna Ahuja and Jason H. Moore Tags: Research Source Type: research
Identification of influential observations in high-dimensional cancer survival data through the rank product test
Survival analysis is a statistical technique widely used in many fields of science, in particular in the medical area, and which studies the time until an event of interest occurs. Outlier detection in this co... (Source: BioData Mining)
Source: BioData Mining - February 14, 2018 Category: Bioinformatics Authors: Eunice Carrasquinha, Andr é Veríssimo, Marta B. Lopes and Susana Vinga Tags: Research Source Type: research
Scalable non-negative matrix tri-factorization
Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disea... (Source: BioData Mining)
Source: BioData Mining - December 29, 2017 Category: Bioinformatics Authors: Andrej Čopar, Marinka žitnik and Blaž Zupan Tags: Research Source Type: research
An automated pipeline for bouton, spine, and synapse detection of in vivo two-photon images
In the nervous system, the neurons communicate through synapses. The size, morphology, and connectivity of these synapses are significant in determining the functional properties of the neural network. Therefo... (Source: BioData Mining)
Source: BioData Mining - December 20, 2017 Category: Bioinformatics Authors: Qiwei Xie, Xi Chen, Hao Deng, Danqian Liu, Yingyu Sun, Xiaojuan Zhou, Yang Yang and Hua Han Tags: Research Source Type: research
TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps
Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve... (Source: BioData Mining)
Source: BioData Mining - December 19, 2017 Category: Bioinformatics Authors: J. Grey Monroe, Zachariah A. Allen, Paul Tanger, Jack L. Mullen, John T. Lovell, Brook T. Moyers, Darrell Whitley and John K. McKay Tags: Software article Source Type: research
Sparse generalized linear model with L 0 approximation for feature selection and prediction with big omics data
Feature selection and prediction are the most important tasks for big data mining. The common strategies for feature selection in big data mining are L 1, SCAD and MC+. However, none of... (Source: BioData Mining)
Source: BioData Mining - December 19, 2017 Category: Bioinformatics Authors: Zhenqiu Liu, Fengzhu Sun and Dermot P. McGovern Tags: Methodology Source Type: research
Cluster ensemble based on Random Forests for genetic data
Clustering plays a crucial role in several application domains, such as bioinformatics. In bioinformatics, clustering has been extensively used as an approach for detecting interesting patterns in genetic data... (Source: BioData Mining)
Source: BioData Mining - December 15, 2017 Category: Bioinformatics Authors: Luluah Alhusain and Alaaeldin M. Hafez Tags: Methodology Source Type: research
PMLB: a large benchmark suite for machine learning evaluation and comparison
The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world ... (Source: BioData Mining)
Source: BioData Mining - December 11, 2017 Category: Bioinformatics Authors: Randal S. Olson, William La Cava, Patryk Orzechowski, Ryan J. Urbanowicz and Jason H. Moore Tags: Research Source Type: research
Ten quick tips for machine learning in computational biology
Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experi... (Source: BioData Mining)
Source: BioData Mining - December 8, 2017 Category: Bioinformatics Authors: Davide Chicco Tags: Review Source Type: research
Artificial intelligence: more human with human
(Source: BioData Mining)
Source: BioData Mining - December 1, 2017 Category: Bioinformatics Authors: Moshe Sipper and Jason H. Moore Tags: Editorial Source Type: research
OCDD: an obesity and co-morbid disease database
Obesity is a medical condition that is known for increased body mass index (BMI). It is also associated with chronic low level inflammation. Obesity disrupts the immune-metabolic homeostasis by changing the se... (Source: BioData Mining)
Source: BioData Mining - November 21, 2017 Category: Bioinformatics Authors: Indrani Ray, Anindya Bhattacharya and Rajat K. De Tags: Research Source Type: research
Metrics to estimate differential co-expression networks
Detecting the differences in gene expression data is important for understanding the underlying molecular mechanisms. Although the differentially expressed genes are a large component, differences in correlati... (Source: BioData Mining)
Source: BioData Mining - November 10, 2017 Category: Bioinformatics Authors: Elpidio-Emmanuel Gonzalez-Valbuena and V íctor Treviño Tags: Methodology Source Type: research
