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MicroRNAs (miRNAs) are short regulatory RNAs derived from longer precursor RNAs. miRNA biogenesis has been studied in animals and plants, recently elucidating more complex aspects, such as non-conserved, speci...
Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software packag...
Inferring gene networks from high-throughput data constitutes an important step in the discovery of relevant regulatory relationships in organism cells. Despite the large number of available Gene Regulatory Ne...
Analyzing the three-dimensional (3D) refractive index distribution of a single cell makes it possible to describe and characterize its inner structure in a marker-free manner. A dense, full-view tomographic da...
Network component analysis (NCA) became a popular tool to understand complex regulatory networks. The method uses high-throughput gene expression data and a priori topology to reconstruct transcription factor ...
Predicting drug side effects is an important topic in the drug discovery. Although several machine learning methods have been proposed to predict side effects, there is still space for improvements. Firstly, t...
Our publication of the BitTorious portal [1] demonstrated the ability to create a privatized distributed data warehouse of sufficient magnitude for real-world bioinformatics studies using minimal changes to the s...
Prediction models are used in clinical research to develop rules that can be used to accurately predict the outcome of the patients based on some of their characteristics. They represent a valuable tool in the...
The field of metagenomics (study of genetic material recovered directly from an environment) has grown rapidly, with many bioinformatics analysis methods being developed. To ensure appropriate use of such meth...
MiRNAs play a critical role in the response of plants to abiotic and biotic stress. However, the functions of most plant miRNAs remain unknown. Inferring these functions from miRNA functional similarity would ...
RNA-seq is a powerful tool for measuring transcriptomes, especially for identifying differentially expressed genes or transcripts (DEGs) between sample groups. A number of methods have been developed for this ...
The central element of each enzyme is the catalytic site, which commonly catalyzes a single biochemical reaction with high specificity. It was unclear to us how often sites that catalyze the same or highly sim...
Some of the current software tools for comparative metagenomics provide ecologists with the ability to investigate and explore bacterial communities using α– & β–diversity. Feature subset selection – a sub-field ...
Over the last decade, next generation sequencing (NGS) has become widely available, and is now the sequencing technology of choice for most researchers. Nonetheless, NGS presents a challenge for the evolutiona...
Bacterial operons are considerably more complex than what were thought. At least their components are dynamically rather than statically defined as previously assumed. Here we present a computational study of ...
In the context of infectious disease, sequence clustering can be used to provide important insights into the dynamics of transmission. Cluster analysis is usually performed using a phylogenetic approach whereb...
Small RNA-sequencing has revealed the diversity and high abundance of small RNAs derived from tRNAs, referred to as tRNA-derived RNAs. However, at present, there is no standardized nomenclature and there are n...
The intracellular environment is a complex and crowded medium where the diffusion of proteins, metabolites and other molecules can be decreased. One of the most popular methodologies for the simulation of diff...
Supplementary material is a ubiquitous feature of scientific articles, particularly in journals that limit the length of the articles. While the judicious use of supplementary material can improve the readabil...
Identification of biological specimens is a requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but generally do not scale to...
Numerous tools have been developed to predict the fitness effects (i.e., neutral, deleterious, or beneficial) of genetic variants on corresponding proteins. However, prediction in terms of whether a variant ca...
The Turku Event Extraction System (TEES) is a text mining program developed for the extraction of events, complex biomedical relationships, from scientific literature. Based on a graph-generation approach, the...
Modern methods for mining biomolecular interactions from literature typically make predictions based solely on the immediate textual context, in effect a single sentence. No prior work has been published on ex...
We participated in the BioNLP 2013 shared tasks on event extraction. Our extraction method is based on the search for an approximate subgraph isomorphism between key context dependencies of events and graphs o...
Relation extraction is an essential procedure in literature mining. It focuses on extracting semantic relations between parts of text, called mentions. Biomedical literature includes an enormous amount of text...
Pathway analysis methods, in which differentially expressed genes are mapped to databases of reference pathways and relative enrichment is assessed, help investigators to propose biologically relevant hypothes...
ChIP-seq experiments are widely used to detect and study DNA-protein interactions, such as transcription factor binding and chromatin modifications. However, downstream analysis of ChIP-seq data is currently r...
Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional v...
Recently, rapid improvements in technology and decrease in sequencing costs have made RNA-Seq a widely used technique to quantify gene expression levels. Various normalization approaches have been proposed, ow...
Functional annotation of genes and gene products is a major challenge in the post-genomic era. Nowadays, gene function curation is largely based on manual assignment of Gene Ontology (GO) annotations to genes ...
A rapidly growing amount of knowledge about signaling and gene regulatory networks is available in databases such as KEGG, Reactome, or RegulonDB. There is an increasing need to relate this knowledge to high-t...
Orientation and the degree of isotropy are important in many biological systems such as the sarcomeres of cardiomyocytes and other fibrillar structures of the cytoskeleton. Image based analysis of such structu...
Amplicon re-sequencing based on the automated Sanger method remains popular for detection of single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (InDels) for a spectrum of genetics appl...
Reconstruction of neuron anatomy structure is a challenging and important task in neuroscience. However, few algorithms can automatically reconstruct the full structure well without manual assistance, making i...
Metabolomics experiments often comprise large numbers of biological samples resulting in huge amounts of data. This data needs to be inspected for plausibility before data evaluation to detect putative sources...
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