SCALE THE MOUNTAIN FROM DATA TO DECISIONS
You generate vast amounts of biological data—mountains of it. Extracting discoveries from that data to accelerate research and improve clinical decisions requires combined expertise in machine learning, large-scale data analysis, and biology. Ridgeline Computational Biology combines these disciplines—backed by decades of experience—to derive meaningful insight from complex data. As AI becomes central to analysis, its value depends on choosing the right tools, knowing when to trust them, and recognizing when they fail. Anybody can run your data through a pipeline or an AI Chatbot—you need a partner who understands your goals and can help you chart the course to reach them.
HOW RIDGELINE CAN HELP
Ridgeline provides hands-on computational biology support to biotech and pharma, from one-off data analyses to ongoing strategic guidance.
Ridgeline Computational Biology is Gene Cutler, PhD. You work directly with an experienced computational biologist from start to finish.
ANALYZE YOUR DATA
Hands-on analysis of complex experimental and clinical datasets.
Typical work: biomarker analysis, omics interpretation, stand-alone study support.
BUILD YOUR CAPABILITIES
Design in-house and outsourced computational biology and machine learning capabilities.
Typical work: workflows, team structure, vendor selection, analytical infrastructure.
SHAPE YOUR STRATEGY
High-level guidance on where and how to apply computational biology and AI.
Typical work: portfolio decisions, translational strategy, study design, fit-for-purpose AI.
Selected Clients
EXPERIENCE
Ridgeline’s goal is to extract biological stories from big data. Principal, Gene Cutler has extensive experience in drug development across a range of therapeutic areas from discovery to the clinic. Having been trained as a molecular biologist but with extensive experience in programming and machine learning, Dr. Cutler know which questions to ask and which results are meaningful.
CAREER HISTORY
25+ years in drug discovery across Amgen, FLX Bio, RAPT Therapeutics, and Ridgeline Computational Biology — from target identification to clinical biomarker strategy.
Read full history →EDUCATION
PhD in Molecular and Cell Biology, UC Berkeley. BA in Biology, Cornell University.
View credentials →PUBLICATIONS & PATENTS
Peer-reviewed research and patents spanning oncology, immuno-oncology, genomics, and computational biology.
View complete list →Publications
Dr. Cutler has co-authored numerous research articles:
2022 | cited by 31
EBV+ tumors exploit tumor cell-intrinsic and -extrinsic mechanisms to produce regulatory T cell-recruiting chemokines CCL17 and CCL22
2020 | cited by 163
Tumors establish resistance to immunotherapy by regulating Treg recruitment via CCR4
2020 | cited by 40
Novel, selective inhibitors of USP7 uncover multiple mechanisms of antitumor activity in vitro and in vivo
2020 | cited by 26
Novel piperidinyl-azetidines as potent and selective CCR4 antagonists elicit antitumor response as a single agent and in combination with checkpoint inhibitors
2019 | cited by 40
Discovery of a potent and selective CCR4 antagonist that inhibits Treg trafficking into the tumor microenvironment
2010 | cited by 34
Molecular signatures of the primitive prostate stem cell niche reveal novel mesenchymal-epithelial signaling pathways
2010 | cited by 62
Identification of transcriptional networks responding to pyrroloquinoline quinone dietary supplementation and their influence on thioredoxin expression, and the JAK/STAT and other pathways
2009 | cited by 87
Molecular signatures of prostate stem cells reveal novel signaling pathways and provide insights into prostate cancer
2008 | cited by 26
Copy number variation in the mouse genome: implications for the mouse as a model organism for human disease
2007 | cited by 117
Significant gene content variation characterizes the genomes of inbred mouse strains
2005 | cited by 222
Multiclass cancer classification and biomarker discovery using GA-based algorithms
2005 | cited by 239
Hepatocyte growth factor is a preferred in vitro substrate for human hepsin, a membrane-anchored serine protease implicated in prostate and ovarian cancers
2001 | cited by 262
Identification and characterization of a melanin-concentrating hormone receptor