Ratings and Reviews 0 Ratings
Ratings and Reviews 0 Ratings
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OmicsBox stands out as a premier bioinformatics platform that delivers comprehensive data analysis capabilities for genomes, transcriptomes, and metagenomes, in addition to facilitating genetic variation research. This software, widely adopted by prominent research institutions globally, enables scientists to handle extensive and complex datasets while optimizing their analytical workflows. Its design emphasizes efficiency and user-friendliness, providing robust tools that help extract meaningful biological insights from omics data.
The application is segmented into various modules, each tailored with distinct tools and functionalities aimed at conducting specific analyses, including de novo genome assembly, genetic variation assessments, differential expression evaluations, and taxonomic classifications of microbiomes, along with insightful result interpretations and engaging visualizations. Notably, the functional analysis module incorporates the well-regarded Blast2GO annotation method, making OmicsBox an excellent resource for research involving non-model organisms, thereby broadening its applicability in the scientific community. This versatility positions OmicsBox as an essential tool for researchers looking to advance their understanding of complex biological systems.
What is JADBio AutoML?
JADBio is an automated machine learning platform that leverages advanced technology to facilitate machine learning without the need for programming skills. It addresses various challenges in the field of machine learning through its cutting-edge algorithms. Designed for ease of use, it enables users to conduct complex and precise analyses regardless of their background in mathematics, statistics, or coding. Tailored specifically for life science data, especially in the realm of molecular data, it adeptly manages challenges associated with low sample sizes and the presence of high-dimensional measurements that can number in the millions. For life scientists, it is crucial to pinpoint predictive biomarkers and features while gaining insights into their significance and contributions to understanding molecular mechanisms. Furthermore, the process of knowledge discovery often holds greater importance than merely creating a predictive model. JADBio places a strong emphasis on feature selection and interpretation, ensuring that users can extract meaningful insights from their data. This focus enables researchers to make informed decisions based on their findings.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
Has API
API Availability
Has API
Pricing Information
€100/month/seat
Free Trial Offered?
Free Version
Pricing Information
Free
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
BioBam Bioinformatics S.L.
Date Founded
2011
Company Location
Spain
Company Website
www.biobam.com
Company Facts
Organization Name
JADBio
Date Founded
2019
Company Location
United States
Company Website
jadbio.com
Categories and Features
Categories and Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis