9.936 hasil
Menampilkan 1–20 · 0,34 detik · RSS
BMC Bioinformatics
Scopus
ISSN 1471-2105 · BMC · 9.936 artikel di indeks
-
Artikel Jurnal
Limblab: pipeline for 3D analysis and visualisation of limb bud gene expression
Abstract Background Although some aspects of limb development can be treated as a 2D problem, a true understanding of the morphogenesis and patterning requires 3D analysis. Since the data on gene expression patterns are largely static 3D image stacks, a major challenge is an efficient pipeline for…
-
Artikel Jurnal
Benchmarking of methods to analyse data derived from GBS-MeDIP
Abstract Background Genotyping-by-Sequencing with Methylated DNA Immunoprecipitation (GBS-MeDIP) is an emerging method for cost-effective DNA methylation analysis. However, due to its unique sequencing output, conventional bioinformatics pipelines used for RNA-seq and MeDIP-seq are not fully…
-
Artikel Jurnal
Frag’n’Flow: automated workflow for large-scale quantitative proteomics in high performance computing environments
Abstract Background Analysing large-scale mass spectrometry-based complex proteomics datasets often overwhelm desktop computational resources and require manual configuration for analysis. While FragPipe delivers rapid peptide identification across diverse sample preparation and acquisition modes…
-
Artikel Jurnal
Comic: explainable drug repurposing via contrastive masking for interpretable connections
Abstract Many diseases worldwide remain untreated due to the slow and expensive process of drug development. Repurposing existing FDA-approved drugs offers a faster solution, especially with the assistance of artificial intelligence. Despite advancements in AI-driven drug repurposing, current…
-
Artikel Jurnal
SPAC: a scalable and integrated enterprise platform for single-cell spatial analysis
Abstract Background Advancements in spatially resolved single-cell technologies are transforming our understanding of tissue architecture and disease microenvironments. However, analyzing the resulting high-dimensional, gigabyte-scale datasets remains challenging due to fragmented workflows…
-
Artikel Jurnal
QuAPPro: an R shiny app for quantification and alignment of polysome profiles
Abstract Background Polysome profiling is a widespread technique to study mRNA translation. After separation of cellular particles by ultracentrifugation on a sucrose-density gradient, a UV absorbance profile is recorded during elution, which mostly reflects RNA content and shows distinct peaks for…
-
Artikel Jurnal
Integration of bulk RNA-seq pipeline metrics for assessing low-quality samples
Abstract Background With the rise of RNA-seq as an essential and ubiquitous tool for biomedical research, the need for guidelines on quality control (QC) is pressing. Specifically, there remains limited data as to which technical metrics are most informative in identifying low-quality samples…
-
Artikel Jurnal
Design and evaluation of semantically-valid negative samples integration techniques for scalable semi-automated drug repurposing prediction pipelines in rare disease research
Abstract Background Computational approaches involving complex data structures (e.g. machine learning, knowledge graphs) have been more prominent in biological studies for the last two decades. Due to increasingly larger amounts of data collected with modern omics techniques, there is a need for…
-
Artikel Jurnal
Contrastive learning in both structure and function spaces improve drug-target interaction prediction
Abstract Background Identifying drug–target interactions (DTIs) is essential in drug discovery and repositioning. Recently, deep learning has become the mainstream methodology for DTI prediction. However, the scarcity of three-dimensional structural data has forced almost all methods to predict…
-
Artikel Jurnal
Transplatformer: translating toxicogenomic profiles between generations of platforms
Abstract Background Transcriptomic profiling technologies have advanced the analysis of biological and toxicological responses. However, substantial differences in probe design, dynamic range, gene coverage, and preprocessing pipelines across platforms introduce artifacts that limit cross-study…
-
Artikel Jurnal
MUUMI: an R package for statistical and network-based meta-analysis for multi-omics data integration
Abstract Background Disentangling physiopathological mechanisms of biological systems through high-level integration of omics data has become a standard procedure in life sciences. However, platform heterogeneity, batch effects, and the lack of unified methods for single- and multi-omics analyses…
-
Artikel Jurnal
PLysPTM-HGNN: predicting lysine PTM sites of proteins using hybrid graph neural networks
Abstract Background Protein post-translational modification (PTM) is a critical biological process that occurs after protein synthesis and has key roles in several biological processes. Among these, lysine modifications include multiple types and have received considerable attention. Most existing…
-
Artikel Jurnal
Identification of differentially expressed genes in RNA-seq data via semi-rigid orthogonal sparse KL-NMTF
Abstract Background Advances in transcriptome profiling have greatly improved the ability to study gene expression at a genome-wide level. Among the most widely used approaches, RNA sequencing (RNA-seq) offers high resolution, a wide dynamic range of gene expression levels, and reduced technical…
-
Artikel Jurnal
From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture
Abstract Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by…
-
Artikel Jurnal
EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning
Abstract Background DNA sequences are fundamental carriers of genetic information, and their accurate classification is essential for understanding gene regulation, disease mechanisms, and translational genomics. Existing encoding methods often fail to capture both local and long-range dependencies…
-
Artikel Jurnal
MODCAN: driver gene identification based on multi-omics features and differential co-association networks for tumor subtypes
Abstract Background Despite the identification of some pan-cancer driver genes through international collaborative initiatives, the discovery of key cancer driver genes remains a formidable challenge. This limitation continues to hinder progress in critical areas, such as early diagnosis…
-
Artikel Jurnal
MIMI: Molecular Isotope Mass Identifier for stable isotope-labeled Fourier transform ultra-high mass resolution data analysis
Abstract Background Ultra High Resolution (UHR) mass spectrometry systems with Fourier Transform Ion Cyclotron Resonance (FT-ICR) are often used to analyze the composition of complex mixtures of naturally-occurring or isotopically-enriched small molecules, such as metabolite samples for…
-
Artikel Jurnal
Predicting the pathway involvement of metabolites annotated in the MetaCyc knowledgebase
Abstract Background The associations of metabolites with biochemical pathways are highly useful information for interpreting molecular datasets generated in biological and biomedical research. However, such pathway annotations are sparse in most molecular datasets, limiting their utility for…
-
Artikel Jurnal
CMsiRNAdb: a database of chemically modified SiRNA silencing efficiency for nucleic acid drug design
Abstract Background Small interfering RNA (siRNA) is a powerful tool for gene silencing, but its clinical application is limited by instability and potential immunogenicity. While chemical modification is essential to overcome these hurdles, data on chemically modified siRNAs are currently…
-
Artikel Jurnal
Hgtsynergy: a transfer learning method for predicting anticancer synergistic drug combinations based on a drug-drug interaction heterogeneous graph
Abstract Background Drug combination therapy often outperforms monotherapy in cancer treatment, but the vast number of available drugs makes manual screening for synergistic combinations costly. Computational methods, especially deep learning, can reduce the search space by predicting likely…
Menampilkan maksimal 50 halaman. Persempit pencarian dengan filter untuk hasil yang lebih spesifik.