PLOS Computational Biology

by Julie Y. L. Chow, Hilary J. Don, Ben Colagiuri, Evan J. Livesey

Associative learning models have traditionally simplified contingency learning by relying on binary classification of cues and outcomes, such as administering a medical treatment (or not) and observing whether the patient recovered (or not). While successful in capturing fundamental learning phenomena acr...

by Scott L. Nuismer, Christopher H. Remien, Bruno Ghersi, Jenna Nichols, James Bangura, Emmanuel Amara, Marilyn C. Kanu, Osman T. Kanu, Edwin G. Lavalie, Mohamed Turay, Patrick L. K. Swaray, Mohamed A. Vandi, Joseph Hughes, Heinz Feldmann, Kyle Rosenke, Michael A. Jarvis, Andrew J. Davison

Lassa fever is a viral zoonotic disease that sickens tens of thousands of people e...

by Ren Qi, Wenjie Teng, Xin Yang, Peng Han, Alexey K. Shaytan, Bin Liu

Precision oncology requires resolving intratumoral heterogeneity to identify drug-resistant cell states associated with treatment failure and relapse. Although single-cell RNA sequencing enables characterization of heterogeneous resistance-associated states, single-cell drug-response phenotype predict...

by Maarten J. Droste, Robert Planqué, Frank J. Bruggeman

Many heterotrophic microorganisms gradually replace an energetically-efficient mode of metabolism by an inefficient, more wasteful overflow metabolism above a critical growth rate, even though the energy demand continues to rise with growth rate. For instance, complete respiration of a sugar is replaced by its ferm...

by Kexin Ma, Ningjing Wang, Zai Yang, Robert A. Cheke, Biao Tang

Adaptive cancer therapy seeks to modulate aggressive treatment to preserve drug-sensitive tumor cells that suppress resistant populations, but existing strategies often rely on frequent treatment decisions enabled by intensive surveillance, limiting clinical feasibility. Here, we propose a clinically motiva...