2.6k citations · 2.7k across the 6 of their papers we have counts for
6 papers
Contrastive losses as generalized models of global epistasis
David H. Brookes, Jakub Otwinowski, Sam Sinai
Fitness functions map large combinatorial spaces of biological sequences to properties of interest. Inferring these multimodal functions from experimental data is a central task in…
A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization
David H. Brookes, Akosua Busia, Clara Fannjiang +2
We show that a large class of Estimation of Distribution Algorithms, including, but not limited to, Covariance Matrix Adaption, can be written as a Monte Carlo Expectation-Maximiza…
Conditioning by adaptive sampling for robust design
David H. Brookes, Hahnbeom Park, Jennifer Listgarten
We present a new method for design problems wherein the goal is to maximize or specify the value of one or more properties of interest. For example, in protein design, one may wish…
Design by adaptive sampling
David H. Brookes, Jennifer Listgarten
We present a probabilistic modeling framework and adaptive sampling algorithm wherein unsupervised generative models are combined with black box predictive models to tackle the pro…
Improvements to the APBS biomolecular solvation software suite
Elizabeth Jurrus, Dave Engel, Keith Star +21
The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact i…
PB-AM: An Open-Source, Fully Analytical Linear Poisson-Boltzmann Solver
Lisa E. Feldberg, David H. Brookes, Eng-Hui Yap +3
We present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized Poisson Boltzmann equation, for m…