Citation Impact 2023
Journal Impact Factor: 4.0
5-year Journal Impact Factor: 3.7
Source Normalized Impact per Paper (SNIP): 1.413
SCImago Journal Rank (SJR): 0.958
Speed 2023
Submission to first editorial decision (median days): 15
Submission to acceptance (median days): 171
Usage 2023
Downloads: 400,374
Altmetric mentions: 146
Articles
Page 9 of 10
-
Citation: BioData Mining 2013 6:10
-
A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection
Applying a statistical method implies identifying underlying (model) assumptions and checking their validity in the particular context. One of these contexts is association modeling for epistasis detection. He...
Citation: BioData Mining 2013 6:9 -
Prediction of Drosophila melanogaster gene function using Support Vector Machines
While the genomes of hundreds of organisms have been sequenced and good approaches exist for finding protein encoding genes, an important remaining challenge is predicting the functions of the large fraction o...
Citation: BioData Mining 2013 6:8 -
Optimization and visualization of the edge weights in optimal assignment methods for virtual screening
Ligand‐based virtual screening plays a fundamental part in the early drug discovery stage. In a virtual screening, a chemical library is searched for molecules with similar properties to a query molecule by me...
Citation: BioData Mining 2013 6:7 -
Using Bayesian networks to discover relations between genes, environment, and disease
We review the applicability of Bayesian networks (BNs) for discovering relations between genes, environment, and disease. By translating probabilistic dependencies among variables into graphical models and vic...
Citation: BioData Mining 2013 6:6 -
Genetic variants and their interactions in disease risk prediction – machine learning and network perspectives
A central challenge in systems biology and medical genetics is to understand how interactions among genetic loci contribute to complex phenotypic traits and human diseases. While most studies have so far relie...
Citation: BioData Mining 2013 6:5 -
Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis
Identifying high-order genetics associations with non-additive (i.e. epistatic) effects in population-based studies of common human diseases is a computational challenge. Multifactor dimensionality reduction (...
Citation: BioData Mining 2013 6:4 -
Identification of SNPs associated with variola virus virulence
Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibit...
Citation: BioData Mining 2013 6:3 -
Identification of new biomarker candidates for glucocorticoid induced insulin resistance using literature mining
Glucocorticoids are potent anti-inflammatory agents used for the treatment of diseases such as rheumatoid arthritis, asthma, inflammatory bowel disease and psoriasis. Unfortunately, usage is limited because of...
Citation: BioData Mining 2013 6:2 -
Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction
Multifactor Dimensionality Reduction (MDR) has been widely applied to detect gene-gene (GxG) interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predispo...
Citation: BioData Mining 2013 6:1 -
Multivariate methods and software for association mapping in dose‐response genome‐wide association studies
The large sample sizes, freedom of ethical restrictions and ease of repeated measurements make cytotoxicity assays of immortalized lymphoblastoid cell lines a powerful new in vitro method in pharmacogenomics rese...
Citation: BioData Mining 2012 5:21 -
Application of a spatially-weighted Relief algorithm for ranking genetic predictors of disease
Identification of genetic variants that are associated with disease is an important goal in elucidating the genetic causes of diseases. The genetic patterns that are associated with common diseases are complex...
Citation: BioData Mining 2012 5:20 -
Visualising associations between paired ‘omics’ data sets
Each omics platform is now able to generate a large amount of data. Genomics, proteomics, metabolomics, interactomics are compiled at an ever increasing pace and now form a core part of the fundamental systems...
Citation: BioData Mining 2012 5:19 -
Mining SOM expression portraits: feature selection and integrating concepts of molecular function
Self organizing maps (SOM) enable the straightforward portraying of high-dimensional data of large sample collections in terms of sample-specific images. The analysis of their texture provides so-called spot-c...
Citation: BioData Mining 2012 5:18 -
Molecular network analysis of human microRNA targetome: from cancers to Alzheimer’s disease
MicroRNAs (miRNAs), a class of endogenous small noncoding RNAs, mediate posttranscriptional regulation of protein-coding genes by binding chiefly to the 3’ untranslated region of target mRNAs, leading to trans...
Citation: BioData Mining 2012 5:17 -
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures
Geneticists who look beyond single locus disease associations require additional strategies for the detection of complex multi-locus effects. Epistasis, a multi-locus masking effect, presents a particular chal...
Citation: BioData Mining 2012 5:16 -
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection
Algorithms designed to detect complex genetic disease associations are initially evaluated using simulated datasets. Typical evaluations vary constraints that influence the correct detection of underlying mode...
Citation: BioData Mining 2012 5:15 -
Peer2ref: a peer-reviewer finding web tool that uses author disambiguation
Reviewer and editor selection for peer review is getting harder for authors and publishers due to the specialization onto narrower areas of research carried by the progressive growth of the body of knowledge. ...
Citation: BioData Mining 2012 5:14 -
An automated framework for hypotheses generation using literature
In bio-medicine, exploratory studies and hypothesis generation often begin with researching existing literature to identify a set of factors and their association with diseases, phenotypes, or biological proce...
Citation: BioData Mining 2012 5:13 -
Finding biomarkers in non-model species: literature mining of transcription factors involved in bovine embryo development
Since processes in well-known model organisms have specific features different from those in Bos taurus, the organism under study, a good way to describe gene regulation in ruminant embryos would be a species-spe...
Citation: BioData Mining 2012 5:12 -
Murine colon proteome and characterization of the protein pathways
Most of the current proteomic researches focus on proteome alteration due to pathological disorders (i.e.: colorectal cancer) rather than normal healthy state when mentioning colon. As a result, there are lacks o...
Citation: BioData Mining 2012 5:11 -
Logic minimization and rule extraction for identification of functional sites in molecular sequences
Logic minimization is the application of algebraic axioms to a binary dataset with the purpose of reducing the number of digital variables and/or rules needed to express it. Although logic minimization techniq...
Citation: BioData Mining 2012 5:10 -
Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS
It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether pa...
Citation: BioData Mining 2012 5:9 -
A comparison and evaluation of five biclustering algorithms by quantifying goodness of biclusters for gene expression data
Several biclustering algorithms have been proposed to identify biclusters, in which genes share similar expression patterns across a number of conditions. However, different algorithms would yield different bi...
Citation: BioData Mining 2012 5:8 -
‘MicroRNA Targets’, a new AthaMap web-tool for genome-wide identification of miRNA targets in Arabidopsis thaliana
The AthaMap database generates a genome-wide map for putative transcription factor binding sites for A. thaliana. When analyzing transcriptional regulation using AthaMap it may be important to learn which genes a...
Citation: BioData Mining 2012 5:7 -
How do alignment programs perform on sequencing data with varying qualities and from repetitive regions?
Next-generation sequencing technologies generate a significant number of short reads that are utilized to address a variety of biological questions. However, quite often, sequencing reads tend to have low qual...
Citation: BioData Mining 2012 5:6 -
Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View
Phenome-Wide Association Studies (PheWAS) can be used to investigate the association between single nucleotide polymorphisms (SNPs) and a wide spectrum of phenotypes. This is a complementary approach to Genome...
Citation: BioData Mining 2012 5:5 -
Weighted multiple testing procedures for genomic studies
With the rapid development of biological technology, measurement of thousands of genes or SNPs can be carried out simultaneously. Improved procedures for multiple hypothesis testing when the number of tests is...
Citation: BioData Mining 2012 5:4 -
Global tests of P-values for multifactor dimensionality reduction models in selection of optimal number of target genes
Multifactor Dimensionality Reduction (MDR) is a popular and successful data mining method developed to characterize and detect nonlinear complex gene-gene interactions (epistasis) that are associated with dise...
Citation: BioData Mining 2012 5:3 -
A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization
Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular networ...
Citation: BioData Mining 2012 5:2 -
Caipirini: using gene sets to rank literature
Keeping up-to-date with bioscience literature is becoming increasingly challenging. Several recent methods help meet this challenge by allowing literature search to be launched based on lists of abstracts that...
Citation: BioData Mining 2012 5:1 -
Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers
Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their c...
Citation: BioData Mining 2011 4:26 -
Mining the diseasome
Citation: BioData Mining 2011 4:25 -
An R package implementation of multifactor dimensionality reduction
A breadth of high-dimensional data is now available with unprecedented numbers of genetic markers and data-mining approaches to variable selection are increasingly being utilized to uncover associations, inclu...
Citation: BioData Mining 2011 4:24 -
Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction
Proteins are complex structures made of amino acids having a fundamental role in the correct functioning of living cells. The structure of a protein is the result of the protein folding process. However, the g...
Citation: BioData Mining 2011 4:23 -
Detection of putative new mutacins by bioinformatic analysis using available web tools
In order to characterise new bacteriocins produced by Streptococcus mutans we perform a complete bioinformatic analyses by scanning the genome sequence of strains UA159 and NN2025. By searching in the adjacent ge...
Citation: BioData Mining 2011 4:22 -
Evolving hard problems: Generating human genetics datasets with a complex etiology
A goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacti...
Citation: BioData Mining 2011 4:21 -
Taxon ordering in phylogenetic trees by means of evolutionary algorithms
In in a typical "left-to-right" phylogenetic tree, the vertical order of taxa is meaningless, as only the branch path between them reflects their degree of similarity. To make unresolved trees more informative...
Citation: BioData Mining 2011 4:20 -
DA DA: Degree-Aware Algorithms for Network-Based Disease Gene Prioritization
High-throughput molecular interaction data have been used effectively to prioritize candidate genes that are linked to a disease, based on the observation that the products of genes associated with similar dis...
Citation: BioData Mining 2011 4:19 -
Discrete derivative: a data slicing algorithm for exploration of sharing biological networks between rheumatoid arthritis and coronary heart disease
One important concept in traditional Chinese medicine (TCM) is "treating different diseases with the same therapy". In TCM practice, some patients with Rheumatoid Arthritis (RA) and some other patients with Co...
Citation: BioData Mining 2011 4:18 -
Comprehensive analysis of human microRNA target networks
MicroRNAs (miRNAs) mediate posttranscriptional regulation of protein-coding genes by binding to the 3' untranslated region of target mRNAs, leading to translational inhibition, mRNA destabilization or degradat...
Citation: BioData Mining 2011 4:17 -
Interpol: An R package for preprocessing of protein sequences
Most machine learning techniques currently applied in the literature need a fixed dimensionality of input data. However, this requirement is frequently violated by real input data, such as DNA and protein sequ...
Citation: BioData Mining 2011 4:16 -
Detection of changes in gene regulatory patterns, elicited by perturbations of the Hsp90 molecular chaperone complex, by visualizing multiple experiments with an animation
To make sense out of gene expression profiles, such analyses must be pushed beyond the mere listing of affected genes. For example, if a group of genes persistently display similar changes in expression levels...
Citation: BioData Mining 2011 4:15 -
Mining beyond the exome
Citation: BioData Mining 2011 4:14 -
Preprocessing differential methylation hybridization microarray data
DNA methylation plays a very important role in the silencing of tumor suppressor genes in various tumor types. In order to gain a genome-wide understanding of how changes in methylation affect tumor growth, th...
Citation: BioData Mining 2011 4:13 -
A comparison of machine learning techniques for survival prediction in breast cancer
The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years g...
Citation: BioData Mining 2011 4:12 -
The effects of linkage disequilibrium in large scale SNP datasets for MDR
In the analysis of large-scale genomic datasets, an important consideration is the power of analytical methods to identify accurate predictive models of disease. When trying to assess sensitivity from such ana...
Citation: BioData Mining 2011 4:11 -
Using graph theory to analyze biological networks
Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be do...
Citation: BioData Mining 2011 4:10 -
pGQL: A probabilistic graphical query language for gene expression time courses
Timeboxes are graphical user interface widgets that were proposed to specify queries on time course data. As queries can be very easily defined, an exploratory analysis of time course data is greatly facilitat...
Citation: BioData Mining 2011 4:9 -
A comparison of genomic copy number calls by Partek Genomics Suite, Genotyping Console and Birdsuite algorithms to quantitative PCR
Copy number variants are >1 kb genomic amplifications or deletions that can be identified using array platforms. However, arrays produce substantial background noise that contributes to high false discovery ra...
Citation: BioData Mining 2011 4:8