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The emergence of next-generation sequencing (NGS) marked a revolution in biological research, enabling comprehensive characterization of the transcriptome and detailed analysis of the epigenome landscape. This...
Advanced long-read sequencing technologies, such as those from Oxford Nanopore Technologies and Pacific Biosciences, are finding a wide use in de novo genome sequencing projects. However, long reads typically ...
While alignment has traditionally been the primary approach for establishing homology prior to phylogenetic inference, alignment-free methods offer a simplified alternative, particularly beneficial when handli...
The scarcity of available structural data makes characterizing the binding of T-cell receptors (TCRs) to peptide-Major Histocompatibility Complexes (pMHCs) very challenging. The recent surge in sequencing data...
The effects of microbiota on the host phenotypes can differ substantially depending on their age. Longitudinally measured microbiome data allow for the detection of the age modification effect and are useful f...
Microorganisms are found in almost every environment, including soil, water, air and inside other organisms, such as animals and plants. While some microorganisms cause diseases, most of them help in biologica...
The Mapper algorithm is an essential tool for exploring the data shape in topological data analysis. With a dataset as an input, the Mapper algorithm outputs a graph representing the topological features of th...
The circadian clock is a central driver of many biological and behavioral processes, regulating the levels of many genes and proteins, termed clock controlled genes and proteins (CCGs/CCPs), to impart biologic...
Amino acid sequence characterization is a fundamental part of virtually any protein analysis, and creating concise and clear protein topology schemes is of high importance in proteomics studies. Although numer...
The volume of protein sequence data has grown exponentially in recent years, driven by advancements in metagenomics. Despite this, a substantial proportion of these sequences remain poorly annotated, underscor...
The human microbiome is the collection of microorganisms living on and inside of our bodies. A major aim of microbiome research is understanding the role microbial communities play in human health with the goa...
Background: Protein large language models (LLM) have been used to extract representations of enzyme sequences to predict their function, which is encoded by enzyme commission (EC) numbers. However, a comprehensiv...
Single-cell analysis offers insights into cellular heterogeneity and individual cell function. Cell type annotation is the first and critical step for performing such an analysis. Current methods mostly utiliz...
Advances in high throughput sequencing technologies provide a huge number of genomes to be analyzed. Thus, computational methods play a crucial role in analyzing and extracting knowledge from the data generate...
In the context of multi-omics data analytics for various diseases, transcriptome-wide association studies leveraging genetically predicted gene expression hold promise for identifying novel regions linked to c...
Understanding plant hormonal responses to stress and their transport dynamics remains challenging, limiting advancements in enhancing plant resilience. Our study presents a novel approach that utilizes genetic...
Named entity recognition is a fundamental task in natural language processing. Recognizing entities in biomedical text, known as the BioNER, is particularly crucial for cutting-edge applications. However, BioN...
Advancements in high-throughput sequencing and deep learning have boosted single-cell RNA studies. However, current methods for annotating single-cell data face challenges due to high data sparsity and tedious...
Functional genomics aims to decipher gene function by observing cellular changes when specific genes are disrupted using CRISPR technology. However, these experiments are limited by scalability, as comprehensi...
Mosaic loss of the Y chromosome (mLOY) in circulating leukocytes is the most frequently detected age-related chromosomal mosaic event in men. Current mLOY detection approaches use genotyping arrays and employ ...
Mutational processes of diverse origin leave their imprints in the genome during tumour evolution. These imprints are called mutational signatures and they have been characterised for point mutations, structural ...
Gene-environment (G × E) interactions play a critical role in understanding the etiology of diseases and exploring the factors that affect disease prognosis. There are several challenges in detecting G × E int...
Accurately identifying potential drug-target interactions (DTIs) is a critical step in drug discovery. Multiple heterogeneous biological data provide abundant features for DTI prediction. Many computational me...
Patient data contain a wealth of information that could aid in understanding the onset and progression of disease. However, the task of modelling clinical data, which consist of multiple heterogeneous time ser...
The binding between proteins and ligands plays a crucial role in the field of drug discovery. However, this area currently faces numerous challenges. On one hand, existing methods are constrained by the limite...
Adverse drug reactions (ADRs) are among the global public health events that seriously endanger human life and cause high economic burdens. Therefore, predicting the possibility of their occurrence and taking ...
Over the past decade, the continuous and rapid advances in bioinformatics have led to an increasingly common use of molecular sequence comparison for phylogenetic analysis. However, the use of multi-software a...
Massively parallel reporter assays (MPRAs) are an experimental technology for measuring the activity of thousands of candidate regulatory sequences or their variants in parallel, where the activity of individu...
The global Coronavirus Disease 2019 (COVID-19) pandemic highlighted the need to quickly diagnose infections to identify and prevent viral spread in the population. In response to the pandemic, BioFire Defense ...
Piwi-interacting RNAs (piRNAs) are well established for monitoring and protecting the genome from transposons in germline cells. Recently, numerous studies provided evidence that piRNAs also play important rol...
Gene regulatory networks (GRNs) involve complex regulatory relationships between genes and play important roles in the study of various biological systems and diseases. The introduction of single-cell sequenci...
Alterations of metabolism, including changes in mitochondrial metabolism as well as glutathione (GSH) metabolism are a well appreciated hallmark of many cancers. Mitochondrial GSH (mGSH) transport is a poorly ...
Data adjustment is an essential tool for increasing statistical power during analysis, for example in case of complex multi-experiment data from (single-cell) RNA, proteomics and other omics data. Despite its ...
A massive amount of protein sequences have been obtained, but their functions remain challenging to discern. In recent research on protein function prediction, Protein-Protein Interaction (PPI) Networks have p...
Single-cell technologies enable comprehensive profiling of diverse immune cell-types through the measurement of multiple genes or proteins per individual cell. In order to translate immune signatures assayed f...
Fluorescent Timer proteins, which display time-dependent changes in their emission spectra, are invaluable for analyzing the temporal dynamics of cellular events at the single-cell level. We previously develop...
The original article was published in BMC Bioinformatics 2023 24:204
Accurate segmentation and classification of cell nuclei are crucial for histopathological image analysis. However, existing deep neural network-based methods often struggle to capture complex morphological fea...
Proteins are involved in nearly all cellular functions, encompassing roles in transport, signaling, enzymatic activity, and more. Their functionalities crucially depend on their complex three-dimensional arran...
Multi-omic integration involves the management of diverse omic datasets. Conducting an effective analysis of these datasets necessitates a data management system that meets a specific set of requirements, such...
Multi-omic studies provide comprehensive insight into biological systems by evaluating cellular changes between normal and pathological conditions at multiple levels of measurement. Biological networks, which ...
Atomic force microscopy (AFM) is the gold-standard technique to simultaneously map the morphology and viscoelastic properties of living cells. Although existing software tools, both open-source and from AFM ma...
Biomedical researchers must often deal with large amounts of raw data, and analysis of this data might provide significant insights. However, if the raw data size is large, it might be difficult to uncover the...
Viruses can inhabit their hosts in the form of an ensemble of various mutant strains. Reconstructing a robust consensus representation for these diverse mutant strains is essential for recognizing the genetic ...
Spatial transcriptomics is a state-of-art technique that allows researchers to study gene expression patterns in tissues over the spatial domain. As a result of technical limitations, the majority of spatial t...
Biomedical text mining is a technique that extracts essential information from scientific articles using named entity recognition (NER). Traditional NER methods rely on dictionaries, rules, or curated corpora,...
Single-cell RNA sequencing (scRNA-seq) has transformed biological research by offering new insights into cellular heterogeneity, developmental processes, and disease mechanisms. As scRNA-seq technology advance...
RNA sequencing (RNA-seq) is the conventional genome-scale approach used to capture the expression levels of all detectable genes in a biological sample. This is now regularly used for population-based studies ...
MetaDAG is a web-based tool developed to address challenges posed by big data from omics technologies, particularly in metabolic network reconstruction and analysis. The tool is capable of constructing metabol...
High-throughput behavioral analysis is important for drug discovery, toxicological studies, and the modeling of neurological disorders such as autism and epilepsy. Zebrafish embryos and larvae are ideal for su...
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