Kinney Lab

Sequence-function relationships, machine learning, and the biophysics of gene regulation

Our Research

We study the biophysical mechanisms of gene regulation by quantitatively measuring and modeling sequence-function relationships.

Our experimental work uses massively parallel reporter assays (MPRAs) to measure the effects that variant gene regulatory sequences have on gene expression. We pursue this experimental work in two biological contexts: alternative mRNA splicing in human cells and transcriptional regulation in bacteria.

Our theoretical and computational work develops methods for analyzing the data produced by MPRAs and other highly multiplexed assays. We aim to extract biophysically meaningful models of regulatory sequence function, but also to understand the quantitative nature of sequence-function relationships more broadly. These efforts include deploying robust software for use by the larger genomics community.

Principal Investigator
Justin B. Kinney
Associate Professor
Simons Center for Quantitative Biology
Cold Spring Harbor Laboratory
PhD, Princeton, 2008
Twitter: @jbkinney

Job Openings

Experimental Positions

We are recuiting graduate students and postdocs who are passionate about quantitatively understanding alternative mRNA splicing in humans, as well as the mechanisms by which splice-modifying drugs work. This experimental work is being pursued in partnership with Adrian Krainer (CSHL).

Computational Postions

We are recruiting graduate students and postdocs who are interested in developing computational and mathematical methods for learning sequence-function relationships from multiplex assays of variant effect (MAVEs), which include massively parallel reporter assays and deep mutational scanning experiments. We are especially interested in developing methods that yield insight into the biophysical mechanisms of gene regulation.

Selected Publications

Click here for a complete list of publications on Google Scholar.

Kinney JB, McCandlish DM. Massively parallel assays and quantitative sequence-function relationships Annu. Rev. Genomics Hum. Genet. 20:99-127 (2019).
Wong MS, Kinney JB*, Krainer AR*. Quantitative activity profile and context dependence of all human 5′ splice sites. Mol. Cell 71(6):1012-1026.e3 (2018). *Equal contribution.
Forcier T, Ayaz A, Gill MS, Jones D, Phillips R, Kinney JB. Measuring cis-regulatory energetics in living cells using allelic manifolds eLife 7:e40618 (2018).
Chen W, Tareen A, Kinney JB. Density estimation on small datasets. Phys. Rev. Lett. 121,160605 (2018).
Adams RM, Mora T*, Walczak AM*, Kinney JB*. Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves. eLife 2016;5:e23156 (2016). *Equal contribution.
Kinney JB, Murugan A, Callan CG, Cox EC. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc Natl Acad Sci USA 107(20):9158-9163 (2010).