ArticlePeerJ2018
Venomix: a simple bioinformatic pipeline for identifying and characterizing toxin gene candidates from transcriptomic data.
Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 23 citations in OpenAlex.
- Multi-omics characterization of toxin expression and producing organs in the predatory gastropods Monoplex corrugatus and Stramonita haemastoma.BMC genomics · 2026Article
- ToxIR: an accurate RNA-seq pipeline for high-precision toxin transcriptome profiling, validated in odontobuthus doriae venom glands.Scientific reports · 2025Article
- Lowly Expressed Toxin Transcripts in Poorly Characterized Myanmar Russell's Viper Venom Gland.Biotech (Basel (Switzerland)) · 2025Article
- Distinct regulatory networks control toxin gene expression in elapid and viperid snakes.BMC genomics · 2024Article
- DeTox: a pipeline for the detection of toxins in venomous organisms.Briefings in bioinformatics · 2024Article
- ToxCodAn-Genome: an automated pipeline for toxin-gene annotation in genome assembly of venomous lineages.GigaScience · 2024Article
- Article
- Exploring Toxin Genes of Myanmar Russell's Viper,Toxins · 2023Article
- High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development.Biodesign research · 2022Article
- The holobiont transcriptome of teneral tsetse fly species of varying vector competence.BMC genomics · 2021Article
- Article
- Transcriptomic Profiling Reveals Extraordinary Diversity of Venom Peptides in Unexplored Predatory Gastropods of the Genus Clavus.Genome biology and evolution · 2020Article
- Article
- Pore-Forming Proteins from Cnidarians and Arachnids as Potential Biotechnological Tools.Toxins · 2019Article
- Article
- High Throughput Identification of Novel Conotoxins from the Vermivorous Oak Cone Snail (International journal of molecular sciences · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advent of next-generation sequencing has resulted in transcriptome-based approaches to investigate functionally significant biological components in a variety of non-model organism. This has resulted in the area of "venomics": a rapidly growing field using combined transcriptomic and proteomic datasets to characterize toxin diversity in a variety of venomous taxa. Ultimately, the transcriptomic portion of these analyses follows very similar pathways after transcriptome assembly often including candidate toxin identification using BLAST, expression level screening, protein sequence alignment, gene tree reconstruction, and characterization of potential toxin function. Here we describe the Python package Venomix, which streamlines these processes using common bioinformatic tools along with ToxProt, a publicly available annotated database comprised of characterized venom proteins. In this study, we use the Venomix pipeline to characterize candidate venom diversity in four phylogenetically distinct organisms, a cone snail (Conidae;
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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.