ArticleMethods in molecular biology (Clifton, N.J.)2019
CRM Discovery Beyond Model Insects.
Article in Methods in molecular biology (Clifton, N.J.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 22 citations in OpenAlex.
- Transcriptional regulation of neuropeptide receptors underlies context-dependent adaptation in Drosophila melanogaster.FEBS open bio · 2026Article
- Ecological Niche Adaptations Influence Transposable Element Dynamics in Pollinating and Non-Pollinating Fig Wasps.Ecology and evolution · 2025Article
- Article
- Mechanisms of transcriptional regulation inProceedings. Biological sciences · 2024Article
- Article
- Mechanisms of transcriptional regulation inbioRxiv : the preprint server for biology · 2023Article
- A novel role for trithorax in the gene regulatory network for a rapidly evolving fruit fly pigmentation trait.PLoS genetics · 2023Article
- Identification of new Anopheles gambiae transcriptional enhancers using a cross-species prediction approach.Insect molecular biology · 2021Article
- Annotating the Insect Regulatory Genome.Insects · 2021Review
- Computational enhancer prediction: evaluation and improvements.BMC bioinformatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Although the number of sequenced insect genomes numbers in the hundreds, little is known about gene regulatory sequences in any species other than the well-studied Drosophila melanogaster. We provide here a detailed protocol for using SCRMshaw, a computational method for predicting cis-regulatory modules (CRMs, also "enhancers") in sequenced insect genomes. SCRMshaw is effective for CRM discovery throughout the range of holometabolous insects and potentially in even more diverged species, with true-positive prediction rates of 75% or better. Minimal requirements for using SCRMshaw are a genome sequence and training data in the form of known Drosophila CRMs; a comprehensive set of the latter can be obtained from the SCRMshaw download site. For basic applications, a user with only modest computational know-how can run SCRMshaw on a desktop computer. SCRMshaw can be run with a single, narrow set of training data to predict CRMs regulating a specific pattern of gene expression, or with multiple sets of training data covering a broad range of CRM activities to provide an initial rough regulatory annotation of a complete, newly-sequenced genome.
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.