Engineered local heterogeneity in drug concentration is used as a tool to encode drug treatment regimens and to predict the macroscopic cellular response to drug perturbations.

Data-driven systems biology models of signaling predict cellular response to untested perturbations and can nominate drug combinations to overcome drug resistance in cancer cells.

A novel compartment model identifies the impact of malaria strain diversity on biogeographic drug resistance patterns, supported by empirical evidence.

The transcriptomic profiles of the constituent monotherapies of synergistic drug pairs tend to be correlated and result in novel gene expression in the combinations.

compaRe can be used to optimize cytometric high-parameter immunophenotypic characterization of heterogeneous cell populations.

NICEdrug.ch is a resource allowing systematic and large-scale computational analysis of drug biochemistry, enzymatic targets, and toxicity in the context of cellular metabolism.

Beyond well-recognized individual-level risk factors, HIV and hepatitis C transmission among people who inject drugs are further impacted by social and spatial network composition, and spaces in particular may represent efficient means for disseminating interventions that diffuse through the network.

Combined analyses of transcriptome and chromatin accessibility elucidated the mechanisms underlying cancer cell lines response to antitumor candidates and provided a versatile perturbation-informed basal signature able to predict drug sensitivity.

Loss-of-heterozygosity mutations, but not aneuploidies, are linked to the evolution of drug resistance in Candida albicans isolated from immunocompromised patients.

The molecular mechanism behind how emetine inhibits the ribosome of the human malaria parasite, along with structural details of the complex formed, is revealed at high resolution using cryo-electron microscopy.