Introduction
In the world of biological research, the tidal wave of data is daunting due to the many amazing advancements in sequencing technology and computing power. Yet, mining this data for insight can feel like searching for a needle in a haystack. Machine learning (ML) has the potential to accelerate data analysis, but these tools have typically been out of reach for non-ML experts. However, a groundbreaking solution has emerged: an automated machine learning (AutoML) platform tailored specifically for biologists.
Researchers at the Wyss Institute for Biologically Inspired Engineering at Harvard University and MIT have developed BioAutoMATED, an AutoML platform designed for biologists with limited or no ML experience. This platform, featured in a new paper in Cell, promises to democratize the use of ML in the life sciences, making it accessible to a broader audience.
Democratizing Machine Learning for Biologists
The need for accessible ML tools in biology became apparent when a group of scientists realized that only a handful of experts within their research institute possessed the skills to build and train ML models effectively. They recognized the potential of AI in biological research but understood that the complexity of existing ML tools was a barrier to broader adoption.
BioAutoMATED emerged as a response to this challenge, aiming to empower biologists to harness the power of ML and AutoML without requiring extensive expertise.
BioAutoMATED’s Versatility and Ease of Use
What sets BioAutoMATED apart is its versatility and simplicity. It can work with various biological sequences, including nucleic acids, peptides, and glycans, without the need for users to be ML experts. The platform automates data preprocessing and generates models capable of predicting biological functions solely from sequence data.
BioAutoMATED provides users with insights into their data, helping them determine if additional data is needed for improved results. It highlights which parts of a sequence are most relevant to the model’s predictions, offering valuable biological insights. Additionally, the platform assists in designing new sequences for future experiments.
Real-World Applications
To demonstrate BioAutoMATED’s capabilities, researchers used it to explore RNA sequence variations’ impact on translation efficiency in E. coli bacteria. The platform generated a model that performed on par with models created by ML experts but in a fraction of the time and with minimal user input. BioAutoMATED also proved its worth in peptide and glycan sequence analysis, aiding in antibody binding prediction and classifying glycans into immunogenic and non-immunogenic groups.
The Future of AI in Biology
BioAutoMATED represents a significant leap in integrating AI and ML into the realm of biology. As AI tools become more user-friendly, they have the potential to revolutionize research and problem-solving across various domains. With BioAutoMATED, biologists can explore patterns, ask critical questions, and obtain rapid answers, all within a single, accessible framework.
Conclusion
BioAutoMATED will be immensely impactful for research and development teams in pharma and biotech. Its ability to simplify complex ML analysis opens several new doors for innovation in the life sciences. As machine learning and AI continue to evolve, platforms like BioAutoMATED pave the way for a future where AI becomes a vital collaboration tool for biologists and engineers. With this tool at their disposal, the next generation of researchers can uncover the intricacies of life more efficiently and unlock groundbreaking discoveries in the world of biology.
Outsourcing Bioinformatics Analysis: How Bridge Informatics Can Help
Groundbreaking studies like these are made possible by technological advances making biological data generation, storage and analysis faster and more accessible than ever before. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics can help you on every step of your research journey.
As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.
Haider M. Hassan, Data Scientist, Bridge Informatics
Haider is one of our premier data scientists. He provides bioinformatic services to clients, including high throughput sequencing, data pre-processing, analysis, and custom pipeline development. Drawing on his rich experience with a variety of high-throughput sequencing technologies, Haider analyzes transcriptional (spatial and single-cell), epigenetic, and genetic landscapes.
Before joining Bridge Informatics, Haider was a Postdoctoral Associate at the London Regional Cancer Centre in Ontario, Canada. During his postdoc, he investigated the epigenetics of late-onset liver cancer using murine and human models. Haider holds a Ph.D. in biochemistry from Western University, where he studied the molecular mechanisms behind oncogenesis. Haider still lives in Ontario and enjoys spending his spare time visiting local parks. If you’re interested in reaching out, please email [email protected] or [email protected]
