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.
MutationForecaster® combines 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 .
You can now experience our integrated suite of genome interpretation products through a free trial of MutationForecaster®. Once you register, analyze datasets that we have analyzed in our peer-reviewed publications with any of our software tools.
Ionizing radiation produces characteristic chromosome changes. The altered chromosomes contain two central constrictions, termed centromeres, instead of one (known as dicentric chromosomes [DCs]). Chromosome biodosimetry is approved by the IAEA for occupational radiation exposure, radiation emergencies, or monitoring long term exposures. In emergency responses to a range of doses, labs need efficient methods that identify DCs.
Cytognomix has developed a novel approach to find DCs that is independent of chromosome length, shape and structure from different laboratories (paper: 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 based algorithms with high sensitivity and specificity that 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 all types of commercial metaphase scanning systems, selects high quality cells for analysis, identifies dicentric chromosomes (removing false positives), 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 that others cannot with advanced, patented genomic probe and bioinformatic technologies. Cytognomix continues our long track record of creating technologies for genomic medicine. We anticipate and implement the needs of the biomedical and clinical genomics communities.
Browse the products section of the menu found in the header bar for more information regarding any of our services.
- Don’t want to run your own analyses on MutationForecaster®? Let us do it for you with our Bespoke Analysis Service.
- Customized genomic microarrays
- Ultrahigh resolution FISH probes:
- Microarray-based comparative genomic hybridization (aCGH) can use SC technology to increase reproducibility and reduce cost per sample.
On May 10, 2021, CytoGnomix is presenting a poster at ConRad 2021 (www.radiation-medicine.de) titled: Demonstration of the Automated Dicentric Chromosome Identifier and Dose Estimator [ADCI] System in a Cloud-based, Online Environment. From the abstract: Interpretation of cytogenetic metaphase images and quantification of exposures remain labour intensive in radiation biodosimetry, despite computer-assisted dicentric chromosome (DC) recognition […]
On May 10, 2021, Dr. Rogan is giving a platform presentation at ConRad 2021 (www.radiation-medicine.de) titled “Radiation biodosimetry exposure assessment from gene expression signatures can be confounded by other underlying disease pathologies.” Misclassification of patients with underlying disorders by otherwise accurate radiation gene signatures compromises their utility for population-scale radiation exposure assessment. Underlying conditions modify […]
We have published a new article about accelerating biodosimetry testing in a large scale radiation incident: Rogan PK, Mucaki EJ, Shirley BC, Li Y, Wilkins RC, Norton F, Sevriukova O, Pham N-D, Waller E, Knoll JHM. Automated Cytogenetic Biodosimetry at Population-Scale. Radiation. 2021; 1(2):79-94. doi: 10.3390/radiation1020008 (2021)
CytoGnomix’s first #patent for automated interpretation of #radiation #biodosimetry exposures issued today. US Patent 10,929,641: Smart microscope system for radiation biodosimetry (http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=10929641.PN.&OS=PN/10929641&RS=PN/10929641)
Presentation: “Demonstration of the Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI™) in a Cloud-based Online Environment” at the International Atomic Energy Agency Coordinated Research Project (CRP) E35010: Applications of Biological Dosimetry Methods in Radiation Oncology, Nuclear Medicine, Diagnostic and Interventional Radiology (MEDBIODOSE)
Greetings to you for a safe and healthy New Year. The Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) has become the biodosimetry industry’s leading software system for accurate and rapid quantification of absorbed ionizing radiation. This year we upgraded our Windows-based system to also determine partial body exposures, both fraction of cells exposed and […]
We have published: Pathway‐extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors. Ashis J. Bagchee‐Clark , Eliseos J. Mucaki, Tyson Whitehead, and Peter K. Rogan MedComm (Wiley) 1(3): 311-327, 2020. (https://doi.org/10.1002/mco2.46) Abstract: Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This […]