Powering Computational Biology with ML Models: An Introduction to Our Serving Suite

We are thrilled to introduce our Bio ML Serving Product, a comprehensive platform that delivers APIs for a suite of advanced machine learning models and tools. Our platform is designed to make it easy for users to interact with these models, including comfortable uploading and downloading features through URL link APIs.


RFDiffusion is a state-of-the-art tool designed for gene function prediction. It uses Random Forests and diffusion kernels to predict gene function across various biological networks. By effectively combining network-based methods with machine learning, RFDiffusion provides high-accuracy predictions that can guide researchers in exploring genetic functions and interactions.

MPNN (Message Passing Neural Network)

MPNN is a powerful machine learning model utilized primarily in the realm of chemical informatics. MPNNs leverage graph neural networks to predict molecular properties by passing messages between atoms in a molecule, enabling a nuanced understanding of molecular structures and interactions. This tool is incredibly valuable in drug discovery, allowing researchers to predict the properties of potential drug compounds rapidly.

ESM (Evolutionary Scale Modeling)

ESM is an innovative tool used for protein folding prediction. Using transformer-based models trained on a massive corpus of protein sequences, ESM can predict the structure of proteins with impressive accuracy. In an era where understanding protein structure is critical for drug development and disease understanding, ESM's capabilities prove invaluable.


Progen is a generative model that allows for the de novo design of proteins. It uses deep learning to generate new protein sequences that fold into desired shapes. In essence, Progen allows researchers to 'design' proteins with specific characteristics, opening up vast possibilities in synthetic biology and biomedical engineering.

ProtNLM (Protein Neural Language Model)

ProtNLM is a language model specifically designed for proteins. Trained on a vast dataset of protein sequences, ProtNLM is capable of predicting the 'language' of proteins – the complex sequences of amino acids that determine a protein's structure and function. This understanding can provide critical insights into protein design and function prediction.

Esm Mask LM

Esm Mask LM (Evolutionary Scale Modeling) is a transformer-based model trained on a vast corpus of protein sequences. It excels in predicting the structure of proteins, contributing significantly to our understanding of diseases and drug development.


OmegaFold is a data-driven protein structure prediction tool. Its sophisticated algorithms leverage large-scale protein structure data, enabling the prediction of protein structures with remarkable accuracy.


Tranception is an innovative machine learning model designed for transcription prediction. It's a potent tool for understanding gene expression and the impact of various genetic factors on biological processes.


TM-align is a tool used for protein structure alignment. It is helpful in comparing and aligning protein structures, providing insights into protein function and evolution.

Our Bio ML Serving Product is designed with the end-user in mind. It breaks down the complexity of advanced machine learning models and biological tools, making them easily accessible and usable. By delivering these capabilities through APIs, we aim to empower researchers, bioinformaticians, and anyone interested in computational biology, to make new discoveries, drive innovation, and push the boundaries of our understanding.

And Many More…

Our suite of ML tools doesn't stop here. We constantly strive to include more models and tools that can cater to the diverse needs of the computational biology community.

Our mission is to make these advanced tools available to all, breaking down the barriers of accessibility and knowledge. By serving these models, we hope to empower researchers and accelerate advancements in computational biology. From predicting protein structures to designing new proteins from scratch, the potential applications of these models are as diverse as they are transformative. With these tools at your fingertips, who knows what discoveries you'll make next?


There are many benefits to using our Bio ML serving product, including:

  • Increased efficiency: Our product can automate many tasks that would otherwise be time-consuming and labor-intensive, such as data analysis and hypothesis generation.
  • Increased insights: ML models can provide new insights into biological systems that would not be possible to obtain with traditional methods.
  • Reduced costs: Our product can help to reduce the cost of research by automating tasks and improving accuracy.


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