ArticleComputational and structural biotechnology journal2020
Essential gene prediction in
Article in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed.
- A pan-viral map of host dependency factors from multi-omics integration and machine learning across influenza A, SARS-CoV-2, Zika, and dengue viruses.Journal of translational medicine · 2026Article
- Pathways, outputs and impact of NIH-supported bioinformatics and genomics graduate trainees in Africa.Briefings in bioinformatics · 2026Review
- A hybrid machine learning model with attention mechanism and multidimensional multivariate feature coding for essential gene prediction.BMC biology · 2025Article
- Inference of essential genes inComputational and structural biotechnology journal · 2024Article
- Differentially used codons among essential genes in bacteria identified by machine learning-based analysis.Molecular genetics and genomics : MGG · 2024Article
- Inference of Essential Genes of the ParasiteInternational journal of molecular sciences · 2024Article
- Essential genes identification model based on sequence feature map and graph convolutional neural network.BMC genomics · 2024Article
- Machine learning methods for predicting essential metabolic genes from Plasmodium falciparum genome-scale metabolic network.PloS one · 2024Article
- Artificial intelligence and machine learning applications for cultured meat.Frontiers in artificial intelligence · 2024Review
- Untangling the Context-Specificity of Essential Genes by Means of Machine Learning: A Constructive Experience.Biomolecules · 2023Article
- 'Bingo'-a large language model- and graph neural network-based workflow for the prediction of essential genes from protein data.Briefings in bioinformatics · 2023Article
- Maize Feature Store: A centralized resource to manage and analyze curated maize multi-omics features for machine learning applications.Database : the journal of biological databases and curation · 2023Article
- Integrating massive RNA-seq data to elucidate transcriptome dynamics in Drosophila melanogaster.Briefings in bioinformatics · 2023Article
- Machine learning on large scale perturbation screens for SARS-CoV-2 host factors identifies β-catenin/CBP inhibitor PRI-724 as a potent antiviral.Frontiers in microbiology · 2023Article
- Article
- Identifying essential genes across eukaryotes by machine learning.NAR genomics and bioinformatics · 2021Article
- Cross-Predicting Essential Genes between Two Model Eukaryotic Species Using Machine Learning.International journal of molecular sciences · 2021Article
- Predicting host dependency factors of pathogens inComputational and structural biotechnology journal · 2021Article
- A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification.International journal of molecular sciences · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Genes are termed to be essential if their loss of function compromises viability or results in profound loss of fitness. On the genome scale, these genes can be determined experimentally employing RNAi or knockout screens, but this is very resource intensive. Computational methods for essential gene prediction can overcome this drawback, particularly when intrinsic (e.g. from the protein sequence) as well as extrinsic features (e.g. from transcription profiles) are considered. In this work, we employed machine learning to predict essential genes in
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.