If you're looking for a platform that can automate feature interpretation and model tuning for biomarker discovery in life sciences, JADBio is a top choice. This no-code machine learning platform is geared specifically for automating biomarker discovery and interpretation. It can process multi-omics data and includes features like AutoML, feature interpretation and model tuning. JADBio is particularly useful for researchers studying a variety of conditions, including cancer, immune and endocrine systems, metabolic and chronic diseases, and mental health.
Another top choice is Huma.AI, a generative AI platform geared for life sciences. Although it's geared more for interpreting and analyzing machine learning models, it offers up-to-date results with no character or word limits and complete privacy. Its validated accuracy of 97% and hands-on support from experienced life science and IT professionals make it a good option for medical affairs, clinical development, regulatory affairs and real-world data analysis.
If you're looking for faster medicine discovery, Genesis Therapeutics has the GEMS platform. This AI-based system uses deep learning and molecular simulations to predict properties and generate molecules. It can help researchers and developers discover and develop new drugs for serious diseases by predicting potency, selectivity and ADMET properties.
Last, QIAGEN Digital Insights is a broad bioinformatics software platform that offers expert-curated solutions for genomic and clinical research. It includes tools for analysis, variant assessment and interpretation, making it a good option for biomarker and target discovery, single-cell genomics, gene regulation and microbiome analysis. The platform has been used in many applications and has been cited in thousands of publications.