MutationForecaster® (mutationforecaster.com) is Cytognomix’s patented web-portal for analysis of all types of mutations – coding and non-coding- including interpretation, comparison and management of genetic variant data. It’s a fully automated genome interpretation solution for research, translational and clinical labs.
Run our world-leading genome interpretation software on your exome, gene panel, or complete genome (Shannon transcription factor and splicing pipelines, ASSEDA, Veridical) with the Cytognomix User Variation Database and Variant Effect Predictor. With our integrated suite of software products, analyze coding, non-coding, and copy number variants, and compare new results with existing or your own database. Select predicted mutations by phenotype using articles with CytoVisualization Analytics. With Workflows, automatically perform end-to-end analysis with all of our software products. Download an 1 page overview of MutationForecaster® (link)
Subscribe and analyze your own data via the cloud or… Don’t want to run your own analyses on MutationForecaster®? Let us do it for you with our Bespoke Analysis Service.
Experience our suite of genome interpretation products through a free trial of MutationForecaster®. Once you register, we provide datasets from our peer-reviewed publications to evaluate these software tools.
Automated radiation biodosimetry
Ionizing radiation produces characteristic chromosome changes. The altered chromosomes are known as dicentric chromosomes [DCs]). DC biodosimetry is approved by the IAEA for occupational radiation exposure, radiation emergencies, or monitoring long term exposures. The DC assay can also monitor effects of interventional radiation therapies.
Cytognomix has developed a novel approach to find DCs (TBME). The Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software works on multiple platforms and uses images produced by any of the existing automated metaphase capture systems found in most cytogenetic laboratories. ADCI is now available for for trial or purchase (link). Or contact us for details (pricing).
ADCI* uses machine learning to distinguish monocentric and dicentric chromosomes (Try the Dicentric Chromosome Identifier web app). With novel image segmentation, ADCI has become a fully functional cytogenetic biodosimetry system. ADCI takes images from metaphase scanning systems, selects high quality cells, identifies dicentric chromosomes, builds biodosimetry calibration curves, and estimates exposures. ADCI fulfills the criteria established by the IAEA for accurate triage biodosimetry of a sample in less than an hour. The accuracy is comparable to an experienced cytogeneticist. Check out our online user manual: wiki.
We find and validate mutations and gene signatures that others cannot with advanced, patented genomic bioinformatic technologies. Cytognomix continues our long track record of creating technologies for genomic medicine. We anticipate and implement the needs of the molecular medicine and genomics communities.
Predict chemotherapy outcomes
Pharmacogenomic responses to chemotherapy drugs can be predicted by supervised machine learning of expression and copy number of relevant gene combinations. Since 2015, CytoGnomix has used biochemical evidence to derive gene signatures from changes in gene expression in cell lines, which can subsequently be examined in patients that have been treated with the same drugs. We have derived signatures for 30 different commonly used drugs. Try out out our online predictor: https://chemotherapy.cytognomix.com.
Quantifying responses to ionizing radiation with gene expression signatures.
Gene signatures derived by machine learning have low error rates in externally validated, independent radiation exposed data. They exhibit high specificity and granularity for dose estimation in humans and mice. These signatures can be designed to avoid the effects of confounding, comorbidities which can reduce specificity for detecting radiation exposures. See: https://f1000research.com/articles/7-233/v2
September 9, 2022. Update on US Patent Application “Smart microscope system for radiation biodosimetry”
Our patent application, US Patent Application Serial Number 17/137,317, has had all claims allowed by the US Patent and Trademark office. This application covers the method underlying our ADCI Radiation biodosimetry software system. New claims cover partial body exposures, which are typical in radiation therapy. In addition, this invention covers applications of the technology which […]
Dec. 10, 2021. New preprint about automated radiation cytogenetic biodosimetry in population studies
Radiation Exposure Determination in a Secure, Cloud-based Online Environment Ben C. Shirley, Eliseos J Mucaki, Joan H.M. Knoll, Peter K Rogan bioRxiv 2021.12.09.471993; doi: https://doi.org/10.1101/2021.12.09.471993 #cloud #radiationsafety #radiationprotection
The #Omicron variant of SARS-CoV-2 spreads fast and contact tracing may prove difficult. Here is our new preprint introducing a new geostatistical approach to find disease hotspots earlier: Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada. Authors:Eliseos J. Mucaki, Ben C. Shirley, Peter K Rogan medRxiv 2021.12.06.21267360; doi: https://doi.org/10.1101/2021.12.06.21267360 Figure 8. Multi-node Directional Networks of […]
We have updated our preprint: Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures (https://biorxiv.org/content/10.1101/2021.08.18.456812v3 ) This version of the article has now been accepted for publication in the International Journal of Radiation Biology. (link to: Improved radiation expression profiling…pdf)
Domains in homologous metaphase chromosomes appear to be organized as contiguous sc intervals showing differential accessibility. Furthermore, these domains appear to be conserved along mitotic chromosomes of different germline origins and hematopoietic differentiation states.
Patrick Ostheim, Sally A. Amundson, Christophe Badie, Dimitry Bazyka, Angela C. Evans, Shanaz A. Ghandhi, Maria Gomolka, Milagrosa López Riego, Peter K. Rogan, Robert Terbrueggen, Gayle E. Woloschak, Frederic Zenhausern, Hanns L. Kaatsch, Simone Schüle, Reinhard Ullmann, Matthias Port & Michael Abend (2021) Gene Expression for Biodosimetry and Effect Prediction Purposes: Promises, Pitfalls and Future Directions – […]
The trademark on CytoGnomix MutationForecaster® system has been renewed for another 10 years.
Mucaki, EJ, Shirley BC, and PK Rogan.Improved radiation expression profiling by sequential application of sensitive and specific gene signatures. BioRxiv 2021.08.18.456812. https://doi.org/10.1101/2021.08.18.456812 #artificialintelligence #radiationsafety #geneexpression #genesignature