output
20142026
most citedCREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning

19 citations

9 papers

cs.DB2026

CobbleDB: Modelling Levelled Storage by Composition

Emilie Ma, Ayush Pandey, Annette Bieniusa +1

We present a composition-based approach to building correctby-construction database backing stores. In previous work, we specified the behaviour of several store variants and prove…

math.OC2025

Opportunities for Hybrid Modeling Approaches in Energy Systems optimization

Mohamed Tahar Mabrouk, Shri Balaji Padmanabhan, Bruno Lacarrière +5

This paper surveys the primary computational hurdles of Energy Systems optimization coming from different sources: model-induced complexity, optimization algorithm requirements, an…

cs.DC2025

Energy-Aware Scheduling Strategies for Partially-Replicable Task Chains on Heterogeneous Processors

Yacine Idouar, Adrien Cassagne, Laércio Lima Pilla +7

The arrival of heterogeneous (or hybrid) multicore architectures has brought new performance trade-offs for applications, and efficiency opportunities to systems. They have also in…

q-bio.BM2023★ 19 cited

CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning

Colin A. Grambow, Hayley Weir, Christian N. Cunningham +2

Computational and machine learning approaches to model the conformational landscape of macrocyclic peptides have the potential to enable rational design and optimization. However,…

cs.DB2020

Towards application-specific query processing systems

Dimitrios Vasilas, Marc Shapiro, Bradley King +1

Database systems use query processing subsystems for enabling efficient query-based data retrieval. An essential aspect of designing any query-intensive application is tuning the q…

cs.DC2019

Invariant Safety for Distributed Applications

Sreeja Nair, Gustavo Petri, Marc Shapiro

We study a proof methodology for verifying the safety of data invariants of highly-available distributed applications that replicate state. The proof is (1) modular: one can reason…