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To leverage the potential of multi-omics studies, exploratory data analysis methods that provide systematic integration and comparison of multiple layers of omics information are required. We describe multiple...
Our environment is composed of biological components of varying magnitude. The relationships between the different biological elements can be represented as a biological network. The process of mating in S. cerev...
Since the advent of next-generation sequencing many previously untestable hypotheses have been realized. Next-generation sequencing has been used for a wide range of studies in diverse fields such as populatio...
The expansion of polyglutamine (poly-Q) repeats in several unrelated proteins is associated with at least ten neurodegenerative diseases. The length of the poly-Q regions plays an important role in the progres...
Biological networks connect genes, gene products to one another. A network of co-regulated genes may form gene clusters that can encode proteins and take part in common biological processes. A gene co-expressi...
For decades, mass spectrometry data has been analyzed to investigate a wide array of research interests, including disease diagnostics, biological and chemical theory, genomics, and drug development. Progress ...
Population stratification is a key concern for genetic association analyses. In addition, extreme homogeneity of ethnic origins of a population can make it difficult to interpret how genetic associations in th...
Cellular differentiation during development is controlled by gene regulatory networks (GRNs). This complex process is always subject to gene expression noise. There is evidence suggesting that commonly seen pa...
The mitochondria are essential organelles and are the location of cellular respiration, which is responsible for the majority of ATP production. Each cell contains multiple mitochondria, and each mitochondrion...
Inference of gene regulatory networks (GRNs) from gene microarray expression data is of great interest and remains a challenging task in systems biology. Despite many efforts to develop efficient computational...
Currently available microRNA (miRNA) target prediction algorithms require the presence of a conserved seed match to the 5' end of the miRNA and limit the target sites to the 3' untranslated regions of mRNAs. H...
Error correction is an important step in increasing the quality of next-generation sequencing data for downstream analysis and use. Polymorphic datasets are a challenge for many bioinformatic software packages...
Interactions between the epigenome and structural genomic variation are potentially bi-directional. In one direction, structural variants may cause epigenomic changes in cis. In the other direction, specific loca...
Drug discovery, disease detection, and personalized medicine are fast-growing areas of genomic research. With the advancement of next-generation sequencing techniques, researchers can obtain an abundance of da...
Biomedical semantic role labeling (BioSRL) is a natural language processing technique that identifies the semantic roles of the words or phrases in sentences describing biological processes and expresses them ...
Sharing sets of chemical data (e.g., chemical properties, docking scores, etc.) among collaborators with diverse skill sets is a common task in computer-aided drug design and medicinal chemistry. The ability t...
SNP genotyping microarrays have revolutionized the study of complex disease. The current range of commercially available genotyping products contain extensive catalogues of low frequency and rare variants. Exi...
Several methods are available for the detection of covarying positions from a multiple sequence alignment (MSA). If the MSA contains a large number of sequences, information about the proximities between resid...
The locations of the TM segments inside the membrane proteins are the consequence of a cascade of several events: the localizing of the nascent chain to the membrane, its insertion through the translocon, and ...
The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational ...
Accurate somatic mutation-calling is essential for insightful mutation analyses in cancer studies. Several mutation-callers are publicly available and more are likely to appear. Nonetheless, mutation-calling i...
Many variable selection techniques have been proposed for the clustering of gene expression data. While these methods tend to filter out irrelevant genes and identify informative genes that contribute to a clu...
Genome-wide association studies (GWAS) have successfully identified a large number of single nucleotide polymorphisms (SNPs) that are associated with a wide range of human diseases. However, many of these dise...
Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importan...
In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a ...
High-throughput sequencing has become one of the primary tools for investigation of the molecular basis of disease. The increasing use of sequencing in investigations that aim to understand both individuals an...
Identification of ortholog groups is a crucial step in comparative analysis of multiple genomes. Although several computational methods have been developed to create ortholog groups, most of those methods do n...
Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow a...
Despite the widespread use of high throughput expression platforms and the availability of a desktop implementation of Gene Set Enrichment Analysis (GSEA) that enables non-experts to perform gene set based ana...
Inferring operon maps is crucial to understanding the regulatory networks of prokaryotic genomes. Recently, RNA-seq based transcriptome studies revealed that in many bacterial species the operon structure vary...
Cap analysis of gene expression (CAGE) is a sequencing based technology to capture the 5’ ends of RNAs in a biological sample. After mapping, a CAGE peak on the genome indicates the position of an active trans...
Drug discovery and development has been aided by high throughput screening methods that detect compound effects on a single target. However, when using focused initial screening, undesirable secondary effects ...
Antibiotics are the widely prescribed drugs for children and most likely to be related with adverse reactions. Record on adverse reactions and allergies from antibiotics considerably affect the prescription ch...
Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into accou...
This paper presents multilevel data glyphs optimized for the interactive knowledge discovery and visualization of large biomedical data sets. Data glyphs are three- dimensional objects defined by multiple leve...
Cluster analysis is widely used to discover patterns in multi-dimensional data. Clustered heatmaps are the standard technique for visualizing one-way and two-way clustering results. In clustered heatmaps, rows...
Patterns of disease incidence can identify new risk factors for the disease or provide insight into the etiology. For example, allergies and infectious diseases have been shown to follow periodic temporal patt...
Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multipl...
Finding an efficient method to solve the parameter estimation problem (inverse problem) for nonlinear biochemical dynamical systems could help promote the functional understanding at the system level for signa...
Because of its important effects, as an epigenetic factor, on gene expression and disease development, DNA methylation has drawn much attention from researchers. Detecting differentially methylated loci is an ...
Array based methylation profiling is a cost-effective solution to study the association between genome methylation and human disease & development. Available tools to analyze the Illumina Infinium HumanMethyla...
A means to predict the effects of gene over-expression, knockouts, and environmental stimuli in silico is useful for system biologists to develop and test hypotheses. Several studies had predicted the expression ...
The use of classification algorithms is becoming increasingly important for the field of computational biology. However, not only the quality of the classification, but also its biological interpretation is im...
It is scientifically and ethically imperative that the results of statistical analysis of biomedical research data be computationally reproducible in the sense that the reported results can be easily recapitul...
DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history o...
Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient...
The main goal of the whole transcriptome analysis is to correctly identify all expressed transcripts within a specific cell/tissue - at a particular stage and condition - to determine their structures and to m...
Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and econom...
Simulated nucleotide or amino acid sequences are frequently used to assess the performance of phylogenetic reconstruction methods. BEAST, a Bayesian statistical framework that focuses on reconstructing time-ca...
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Citation Impact 2023
Journal Impact Factor: 2.9
5-year Journal Impact Factor: 3.6
Source Normalized Impact per Paper (SNIP): 0.821
SCImago Journal Rank (SJR): 1.005
Speed 2023
Submission to first editorial decision (median days): 12
Submission to acceptance (median days): 146
Usage 2023
Downloads: 5,987,678
Altmetric mentions: 4,858