Publications.

The team of scientists at Herophilus develops groundbreaking advancements in biotechnology and machine learning. We aim to publish and share our findings with the global research community to collectively advance the fields of neurobiology, disease research and drug discovery.

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Genomics… and AI… then what?

11 August 2022 Herophilus

Every data/AI-driven drug discovery company must eventually do real-world biology experiments. A new class of human in vitro experimental models is ripe to serve this need.

Data science, human intelligence, and therapeutics discovery: An interview with Sean Escola, Saul Kato, and Pavan Ramkumar

8 April 2022 Cell Patterns

Herophilus leaders explain the importance of data science in their research, exploring a score that identifies hierarchical confounder effects in raw data and machine learning-derived data embeddings.

Getting real about curing polygenic brain disease.

1 March 2022 Herophilus

Lone single-target approaches, are doomed to fail in the quest to cure polygenic neurological diseases such as Alzheimer’s, schizophrenia, Parkinson’s, and autisms — ironically, common neurological diseases of high prevalence. A new approach is needed.

RTG: New methods for machine-learning confounder analysis.

22 February 2022 Cell Patterns

Explore how Herophilus approaches hierarchical confounder discovery in the experiment–machine learning cycle in recent paper in Cell Patterns.

Demuxalot: scaled up genetic demultiplexing for single-cell sequencing.

28 May 2021 BioRxiv

Herophilus is working on new methods in transcriptomic analysis. Read about our bioRxiv preprint and open source code release of Demuxalot.

Scaling brain organoids for disease phenotyping.

20 August 2020 bioRxiv

Learn how Herophilus optimizes the scaling of patient-derived brain organoids to uncover deep phenotypes of disease in our bioRxiv preprint.