BioData Mining
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A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactionsAbstract
Background
Non-additive interactions among genes are frequently associated with a number of phenotypes, including known complex diseases such as Alzheimer’s, diabetes, and cardiovascular disease. Detecting interactions requires careful selection of analytical methods, and some machine learn... ...
BioData Mining - - 2021
SequenceCEROSENE: a computational method and web server to visualize spatial residue neighborhoods at the sequence level
BioData Mining - Tập 9 - Trang 1-7 - 2016
To understand the molecular function of biopolymers, studying their structural characteristics is of central importance. Graphics programs are often utilized to conceive these properties, but with the increasing number of available structures in databases or structure models produced by automated modeling frameworks this process requires assistance from tools that allow automated structure visuali......
Representing and querying disease networks using graph databases
BioData Mining - Tập 9 - Trang 1-19 - 2016
Systems biology experiments generate large volumes of data of multiple modalities and this information presents a challenge for integration due to a mix of complexity together with rich semantics. Here, we describe how graph databases provide a powerful framework for storage, querying and envisioning of biological data. We show how graph databases are well suited for the representation of biologic......
mSRFR: a machine learning model using microalgal signature features for ncRNA classification
BioData Mining - Tập 15 - Trang 1-11 - 2022
This work presents mSRFR (microalgae SMOTE Random Forest Relief model), a classification tool for noncoding RNAs (ncRNAs) in microalgae, including green algae, diatoms, golden algae, and cyanobacteria. First, the SMOTE technique was applied to address the challenge of imbalanced data due to the different numbers of microalgae ncRNAs from different species in the EBI RNA-central database. Then the ......
Metrics to estimate differential co-expression networks
BioData Mining - Tập 10 Số 1 - Trang 1-15 - 2017
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 correlation are becoming an interesting approach to achieving deeper insights. However, diverse metrics have been used to detect differential correlation, making selection and use of a single metric d......
Detecting diseases in medical prescriptions using data mining methodsAbstract Every year, the health of millions of people around the world is compromised by misdiagnosis, which sometimes could even lead to death. In addition, it entails huge financial costs for patients, insurance companies, and governments. Furthermore, many physicians’ professional life is adversely affected by unintended errors in prescribing medication or misdia... ...
BioData Mining -
Label-free data standardization for clinical metabolomics
BioData Mining - Tập 10 - Trang 1-12 - 2017
In metabolomics, thousands of substances can be detected in a single assay. This capacity motivates the development of metabolomics testing, which is currently a very promising option for improving laboratory diagnostics. However, the simultaneous measurement of an enormous number of substances leads to metabolomics data often representing concentrations only in conditional units, while laboratory......
The accelerated aging model reveals critical mechanisms of late-onset Parkinson’s diseaseAbstract
Background
Late-onset Parkinson’s disease (LOPD) is a common neurodegenerative disorder and lacks disease-modifying treatments, attracting major attentions as the aggravating trend of aging population. There were numerous evidences supported that accelerated aging was the primary risk facto... ...
BioData Mining - Tập 13 Số 1 - 2020
Integrative analysis of gene expression and methylation data for breast cancer cell lines
BioData Mining - Tập 11 - Trang 1-16 - 2018
The deadly costs of cancer and necessity for an accurate method of early cancer detection have demanded the identification of genetic and epigenetic factors associated with cancer. DNA methylation, an epigenetic event, plays an important role in cancer susceptibility. In this paper, we use DNA methylation and gene expression data integration and pathway analysis to further explore and understand t......
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