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- 1From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-Reviewed
Inference of genomic landscapes using ordered Hidden Markov Models with emission densities (oHMMed).
Background Genomes are inherently inhomogeneous, with features such as base composition, recombination, gene density, and gene expression varying along chromosomes. Evolutionary, biological, and biomedical analyses aim... - 2From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-ReviewedBackground Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target....
- 3From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-ReviewedBackground Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in...
- 4From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-ReviewedBackground Text summarization is a challenging problem in Natural Language Processing, which involves condensing the content of textual documents without losing their overall meaning and information content, In the...
- 5From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-ReviewedBackground MicroRNAs play a critical role in regulating gene expression by binding to specific target sites within gene transcripts, making the identification of microRNA targets a prominent focus of research....
- 6From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-ReviewedBackground The identification of essential proteins can help in understanding the minimum requirements for cell survival and development to discover drug targets and prevent disease. Nowadays, node ranking methods are...
- 7From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-ReviewedBackground With the rapid increase in throughput of long-read sequencing technologies, recent studies have explored their potential for taxonomic classification by using alignment-based approaches to reduce the impact...
- 8From: BMC Bioinformatics. (Vol. 25, Issue 1) Peer-ReviewedBackground High-throughput sequencing is a powerful tool that is extensively applied in biological studies. However, sequencers may produce low-quality bases, leading to ambiguous bases, 'N's. PCR duplicates introduced...
- 9From: BMC Bioinformatics. (Vol. 20, Issue 1) Peer-ReviewedBackground Ontology has attracted substantial attention from both academia and industry. Handling uncertainty reasoning is important in researching ontology. For example, when a patient is suffering from cirrhosis, the...
- 10From: BMC Bioinformatics. (Vol. 20, Issue Suppl 2) Peer-ReviewedBackground Several methods to handle data generated from bottom-up proteomics via liquid chromatography-mass spectrometry, particularly for peptide-centric quantification dealing with post-translational modification...
- 11From: BMC Bioinformatics. (Vol. 20, Issue 1) Peer-ReviewedBackground Canonical correlation analysis (CCA) is a classic statistical tool for investigating complex multivariate data. Correspondingly, it has found many diverse applications, ranging from molecular biology and...
- 12From: BMC Bioinformatics. (Vol. 20, Issue 1) Peer-ReviewedBackground In the last few decades, cumulative experimental researches have witnessed and verified the important roles of microRNAs (miRNAs) in the development of human complex diseases. Benefitting from the rapid...
- 13From: BMC Bioinformatics. (Vol. 20, Issue 1) Peer-ReviewedBackground Many medical imaging techniques utilize fitting approaches for quantitative parameter estimation and analysis. Common examples are pharmacokinetic modeling in dynamic contrast-enhanced (DCE) magnetic...
- 14From: BMC Bioinformatics. (Vol. 19, Issue Suppl 13) Peer-ReviewedBackground Molecular Recognition Features (MoRFs) are short protein regions present in intrinsically disordered protein (IDPs) sequences. MoRFs interact with structured partner protein and upon interaction, they...
- 15From: BMC Bioinformatics. (Vol. 20, Issue 1) Peer-ReviewedBackground Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and...
- 16From: BMC Bioinformatics. (Vol. 20, Issue 1) Peer-ReviewedBackground Although targeted drugs have contributed to impressive advances in the treatment of cancer patients, their clinical benefits on tumor therapies are greatly limited due to intrinsic and acquired resistance of...
- 17From: BMC Bioinformatics. (Vol. 20, Issue Suppl 24) Peer-ReviewedBackground Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery, and many other applications. Chemical fingerprints are a...
- 18From: BMC Bioinformatics. (Vol. 21, Issue 1) Peer-ReviewedBackground In recent years, biomedical ontologies have become important for describing existing biological knowledge in the form of knowledge graphs. Data mining approaches that work with knowledge graphs have been...
- 19From: BMC Bioinformatics. (Vol. 21, Issue Suppl 2) Peer-ReviewedBackground In biomarker discovery, applying domain knowledge is an effective approach to eliminating false positive features, prioritizing functionally impactful markers and facilitating the interpretation of...
- 20From: BMC Bioinformatics. (Vol. 21, Issue 1) Peer-ReviewedBackground Recently developed methods of protein contact prediction, a crucially important step for protein structure prediction, depend heavily on deep neural networks (DNNs) and multiple sequence alignments (MSAs) of...