ArticleJournal of microbiology (Seoul, Korea)2020
User guides for biologists to learn computational methods.
Article in Journal of microbiology (Seoul, Korea), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- A review of Ribosome profiling and tools used in Ribo-seq data analysis.Computational and structural biotechnology journal · 2024Review
- Comparative Transcriptomic Analysis of Flagellar-Associated Genes in Salmonella Typhimurium and Its rnc Mutant.Journal of microbiology (Seoul, Korea) · 2024Article
- Transcript-specific selective translation by specialized ribosomes bearing genome-encoded heterogeneous rRNAs in V. vulnificus CMCP6.Journal of microbiology (Seoul, Korea) · 2022Article
- Regulator of ribonuclease activity modulates the pathogenicity of Vibrio vulnificus.Journal of microbiology (Seoul, Korea) · 2021Article
- Trans-acting regulators of ribonuclease activity.Journal of microbiology (Seoul, Korea) · 2021Review
- Omics-based microbiome analysis in microbial ecology: from sequences to information.Journal of microbiology (Seoul, Korea) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
System-wide studies of a given molecular type are referred to as "omics." These include genomics, proteomics, and metabolomics, among others. Recent biotechnological advances allow for high-throughput measurement of cellular components, and thus it becomes possible to take a snapshot of all molecules inside cells, a form of omics study. Advances in computational modeling methods also make it possible to predict cellular mechanisms from the snapshots. These technologies have opened an era of computation-based biology. Component snapshots allow the discovery of gene-phenotype relationships in diseases, microorganisms in the human body, etc. Computational models allow us to predict new outcomes, which are useful in strain design in metabolic engineering and drug discovery from protein-ligand interactions. However, as the quantity of data increases or the model becomes complicated, the process becomes less accessible to biologists. In this special issue, six protocol articles are presented as user guides in the field of computational biology.
Indexed as
Identifiers
What OpenQuestion holds
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.