Results 151 to 160 of about 132,305 (262)

Limitations of the refolding pipeline for de novo protein design

open access: yesProtein Science, Volume 35, Issue 6, June 2026.
Abstract With the emergence of powerful deep learning‐based tools, computational protein design has become a widely accessible technique. Nowadays, it is possible to perform both sequence and structure design in a matter of minutes, making the technology attractive to the broader scientific community. In protein design campaigns, one of the most common
Kerlen T. Korbeld   +2 more
wiley   +1 more source

Finding Minimum‐Cost Explanations for Predictions Made by Tree Ensembles

open access: yesSoftware: Practice and Experience, Volume 56, Issue 6, Page 615-642, June 2026.
ABSTRACT The ability to reliably explain why a machine learning model arrives at a particular prediction is crucial when used as decision support by human operators of critical systems. The provided explanations must be provably correct, and preferably without redundant information, called minimal explanations.
John Törnblom   +2 more
wiley   +1 more source

A Resource Efficient Ising Model‐Based Quantum Sudoku Solver

open access: yesSoftware: Practice and Experience, Volume 56, Issue 6, Page 643-657, June 2026.
ABSTRACT Background Quantum algorithms exploit superposition and parallelism to address complex combinatorial problems, many of which fall into the non‐polynomial (NP) class. Sudoku, a widely known logic‐based puzzle, is proven to be NP‐complete and thus presents a suitable testbed for exploring quantum optimization approaches.
Wen‐Li Wang   +5 more
wiley   +1 more source

Acellular Fish Skin for Deep Dermal Traumatic Wounds Management: A Case Report. [PDF]

open access: yesClin Case Rep
Biazar E   +6 more
europepmc   +1 more source

Subgroup Identification via Multiple Change Point Detection: Methods and Applications

open access: yesWIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Subgroup identification methods facilitate the discovery of clinically meaningful subpopulations with differing disease progression, improving personalized risk assessment and treatment strategies. ABSTRACT Subgroup identification is a significant research area in statistics and machine learning, aiming to partition a heterogeneous population into more
Yaguang Li   +3 more
wiley   +1 more source

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