Optimize your protein engineering process with our in-silico mutational scanning tool – faster, cost-effective, and fully customizable
Predict Protein Mutations with AI-Powered Precision
Our AI-powered mutational scanning mutational scanning tool helps you accelerate your protein design process by predicting the functional impact of specific mutations without the need for extensive wet-lab experiments. Whether you're designing novel proteins or optimizing existing ones, our tool can scan tens of millions of variants quickly, helping you make informed decisions faster.
Key Features:
- AI-Powered Custom Regression ModelsOur ML models scan vast numbers of variants, predicting mutation effects specific to your protein of interest.
- Minimal Data RequirementGet started with as few as 8-16 data points and improve predictions as you go.
- Confidence IntervalsPredict the potential fitness outcomes of each variant, helping you manage research risks better.
- Efficient VisualizationView a visual distribution of predicted fitness, making it easy to choose the best mutations for further testing.
How it works
Our in-silico mutational scanning tool offers:
- 1Mutation InputEnter the mutations you'd like to evaluate.
- 2Fitness PredictionThe tool predicts the fitness of each variant relative to the wild-type protein.
- 3Fitness VisualizationA clear, interactive interface helps you understand the predicted outcomes.
- 4Iterative LearningUpdate the model with new lab data to continuously improve prediction accuracy.
Benefits of AI-Powered Protein Engineering:
Rapid Results
Speed up the time from hypothesis to results by reducing the need for multiple lab tests.
Cost-Efficient
Lower R&D costs by narrowing down the most promising mutations for testing.
Scalable for Any Protein
Apply the tool to any protein, making it ideal for various research or industrial applications.
Frequently Asked Questions (FAQs)
Our platform harnesses advanced artificial intelligence and machine learning to design, optimize, and engineer proteins tailored to your specific requirements. Whether you need improved enzyme efficiency, novel protein functions, or tailored biotherapeutics, our solutions streamline the protein design process and reduce time-to-market.
Our services are ideal for biotechnology and pharmaceutical companies, academic research labs, industrial manufacturers, and any organization involved in protein-based product development. Applications include enzyme optimization, biocatalyst development, therapeutic protein design, and more.
The process begins with your input data, such as protein sequences, structural information, and desired functional attributes. Our AI algorithms then generate a library of potential protein variants and use predictive modeling to evaluate their stability, activity, and specificity. The top candidates are ranked and provided for further experimental validation, thereby reducing the number of required lab iterations.
Our platform is versatile and can be applied to a wide range of proteins, including enzymes, structural proteins, and therapeutic proteins. We can optimize existing proteins or design novel ones for applications in catalysis, biopharmaceuticals, diagnostics, and more.
Absolutely. We work closely with you to tailor our AI models and algorithms to your target proteins and desired outcomes. This includes integrating proprietary data and fine-tuning parameters to ensure that our platform delivers the most relevant and high-performing protein candidates for your application.
Our platform offers robust API support and standard data export formats (e.g., CSV, JSON) to seamlessly integrate with your Laboratory Information Management Systems (LIMS) and other data analytics pipelines. We also provide comprehensive onboarding and training to ensure a smooth adoption process.
Our models are trained on extensive datasets of protein interactions, structural data, and experimental results. We continuously refine our algorithms with real-world feedback to improve prediction accuracy. While our computational predictions are highly reliable, we recommend subsequent in vitro or in vivo validation to confirm the performance of the engineered proteins.
Yes, we provide collaborative support throughout the validation process. Our team can help design proof-of-concept studies and coordinate with your wet lab partners to verify the performance of our predicted protein variants.
We offer flexible pricing models based on the scope and duration of your project. Options include subscription-based plans for ongoing R&D, as well as project-specific pricing for one-off protein engineering campaigns. Please contact us for a personalized consultation and detailed quote.
Our dedicated customer support team is available to assist you at every stage—from initial onboarding and technical training to troubleshooting and ongoing optimization. We offer support via email, phone, and live chat, along with detailed documentation and a comprehensive FAQ section.
Interested in accelerating your protein research? Contact us for a demo or customized solution.
Neoncorte Bio
Where AI Meets Biotechnology
Neoncorte Bio is at the forefront of the convergence between artificial intelligence and protein engineering. Our team comprises experts in computational biology, bioinformatics, and machine learning, all driven by a mission to accelerate innovation in protein design. By leveraging our advanced AI models, we provide unparalleled solutions that enhance efficiency, reduce costs, and push the boundaries of what's possible in protein engineering
Publications
Scientific Publication of Neoncorte Bio Team
- Modification of natural enzymes to introduce new properties and enhance existing ones is a central challenge in bioengineering. This study is focused on the development of Taq polymerase mutants that show enhanced reverse transcriptase (RTase) activity while retaining other desirable properties such as fidelity, 5′-3′ exonuclease activity, effective deoxyuracil incorporation, and tolerance to locked nucleic acid (LNA)-containing substrates.
- The transcriptomic data are being frequently used in the research of biomarker genes of different diseases and biological states. The most common tasks there are the data harmonization and treatment outcome prediction. Both of them can be addressed via the style transfer approach. Either technical factors or any biological details about the samples which we would like to control (gender, biological state, treatment, etc.) can be used as style components.
- List of all Neoncorte Bio publications dedicated to Molecular Biology, Biotechnology, Artificial Intelligence and Artificial Neural Networks, published mostly by Nikolay Russkikh, CEO of Neoncorte Bio
Our Expertise in Action
With extensive experience in AI applications and software engineering tailored to the life sciences, we specialize in solving complex challenges and delivering innovative solutions for our customers. Our work demonstrates a deep understanding of cutting-edge technologies and their application in the real world.
Here are examples of the types of projects we have successfully delivered:
Here are examples of the types of projects we have successfully delivered:
- Automated NGS Data Analysis:Designed a production-grade solution for the automated processing, annotation, and analysis of Next-Generation Sequencing (NGS) data.
- Single-Cell Data Integration:Built state-of-the-art tools for integrating multimodal single-cell data, achieving recognition for technical excellence.
- Metagenomic Classification Algorithms:Developed advanced methods for classifying sequencing reads in metagenomics research.
- High-Throughput Image Processing Pipelines:Engineered an efficient pipeline to process millions of sequencing images with exceptional accuracy.
- Cell Counting via AI:Created a computer vision solution for precise cell counting in microphotography images, streamlining data analysis.
Get in touch with our team
Phone: +1-503-754-3958
Email: contact@neoncorte.com
Email: contact@neoncorte.com
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contact@neoncorte.com
contact@neoncorte.com