Explainable Multilayer Graph Neural Network for cancer gene prediction. [PDF]
Bioinformatics, 2023 Motivation The identification of cancer genes is a critical yet challenging problem in cancer genomics research. Existing computational methods, including deep graph neural networks, fail to exploit the multilayered gene–gene interactions or provide ...
Chatzianastasis M +2 more
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FragGeneScanRs: faster gene prediction for short reads. [PDF]
BMC Bioinformatics, 2022 FragGeneScan is currently the most accurate and popular tool for gene prediction in short and error-prone reads, but its execution speed is insufficient for use on larger data sets. The parallelization which should have addressed this is inefficient. Its
Van der Jeugt F, Dawyndt P, Mesuere B.
europepmc +2 more sources
Gene prediction in the immunoglobulin loci. [PDF]
Genome Res, 2022 The V(D)J recombination process rearranges the variable (V), diversity (D), and joining (J) genes in the immunoglobulin (IG) loci to generate antibody repertoires. Annotation of these loci across various species and predicting the V, D, and J genes (IG genes) are critical for studies of the adaptive immune system.
Sirupurapu V, Safonova Y, Pevzner PA.
europepmc +3 more sources
Evaluation of Different Gene Prediction Tools in Coccidioides immitis [PDF]
Journal of Fungi, 2023 Gene prediction is required to obtain optimal biologically meaningful information from genomic sequences, but automated gene prediction software is imperfect.
Theo N. Kirkland +2 more
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Lung adenocarcinoma-related target gene prediction and drug repositioning [PDF]
Frontiers in Pharmacology, 2022 Lung cancer is the leading cause of cancer deaths globally, and lung adenocarcinoma (LUAD) is the most common type of lung cancer. Gene dysregulation plays an essential role in the development of LUAD.
Rui Xuan Huang +11 more
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Tiberius: end-to-end deep learning with an HMM for gene prediction. [PDF]
BioinformaticsMotivation For more than 25 years, learning-based eukaryotic gene predictors were driven by hidden Markov models (HMMs), which were directly inputted a DNA sequence. Recently, Holst et al.
Gabriel L, Becker F, Hoff KJ, Stanke M.
europepmc +2 more sources
GeneMark-HM: improving gene prediction in DNA sequences of human microbiome. [PDF]
NAR Genom Bioinform, 2021 Computational reconstruction of nearly complete genomes from metagenomic reads may identify thousands of new uncultured candidate bacterial species. We have shown that reconstructed prokaryotic genomes along with genomes of sequenced microbial isolates ...
Lomsadze A +3 more
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Balrog: A universal protein model for prokaryotic gene prediction. [PDF]
PLoS Comput Biol, 2021 Low-cost, high-throughput sequencing has led to an enormous increase in the number of sequenced microbial genomes, with well over 100,000 genomes in public archives today.
Sommer MJ, Salzberg SL.
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An Ovarian Cancer Susceptible Gene Prediction Method Based on Deep Learning Methods [PDF]
Frontiers in Cell and Developmental Biology, 2021 Ovarian cancer (OC) is one of the most fatal diseases among women all around the world. It is highly lethal because it is usually diagnosed at an advanced stage which may reduce the survival rate greatly.
Lu Ye +4 more
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Long-read microbial genome assembly, gene prediction and functional annotation: a service of the MIRRI ERIC Italian node [PDF]
Frontiers in BioinformaticsBackgroundUnderstanding the structure and function of microbial genomes is crucial for uncovering their ecological roles, evolutionary trajectories, and potential applications in health, biotechnology, agriculture, food production, and environmental ...
Sandro Gepiro Contaldo +11 more
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