Results 81 to 90 of about 522,455 (311)
Molecular Oncology, EarlyView.Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim +3 more
wiley +1 more source
Learning curves for decision making in supervised machine learning: a survey
Learning curves are a concept from social sciences that has been adopted in the context of machine learning to assess the performance of a learning algorithm with respect to a certain resource, e.g., the number of training examples or the number of ...
van Rijn J.N., Mohr F.
core +1 more source
A Machine Learning Potential for Graphene
, 2017 20 Pages (Main text), 6 figures v2. Edited Abstract, removed typos. v3.
Rowe, Patrick +3 more
openaire +2 more sources
Rapid screening of staphylokinase protein variants using an unpurified cell‐free expression system
FEBS Open Bio, EarlyView.An unpurified cell‐free protein synthesis (CFPS) platform enables rapid functional screening of staphylokinase variants. Direct plasminogen‐activation assays performed in microplate format provide real‐time activity readouts, allowing rapid identification and ranking of variants with improved or reduced fibrinolytic activity without protein ...
Maria Tomková +3 more
wiley +1 more source
Machine Learning Potential Repository
, 2020 This paper introduces a machine learning potential repository that includes Pareto optimal machine learning potentials. It also shows the systematic development of accurate and fast machine learning potentials for a wide range of elemental systems.
openaire +2 more sources
Perspective: Machine learning potentials for atomistic simulations [PDF]
The Journal of Chemical Physics, 2016 Nowadays, computer simulations have become a standard tool in essentially all fields of chemistry, condensed matter physics, and materials science. In order to keep up with state-of-the-art experiments and the ever growing complexity of the investigated problems, there is a constantly increasing need for simulations of more realistic, i.e., larger ...
openaire +2 more sources
Current Research in Food ScienceRecently, the application of biosensors in food safety assessment has gained considerable research attention. Nevertheless, the evaluation of biosensors' sensitivity, accuracy, and efficiency is still ongoing.
Zixuan Zhou +7 more
doaj +1 more source
FEBS Open Bio, EarlyView.Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source
Machine learning in energy storage materials
Interdisciplinary Materials, 2022 With its extremely strong capability of data analysis, machine learning has shown versatile potential in the revolution of the materials research paradigm.
Zhong‐Hui Shen +5 more
doaj +1 more source
Why human connection is the true metric of research success
FEBS Open Bio, EarlyView.Human‐centred mentorship can be shaped by mentor attributes, actions, intrinsic drive and career ambition. Drawing on reflections across Singapore and France, as well as workshop insights from FEBS‐IUBMB ENABLE 2024, this article shows that human‐centred mentorship creates the conditions for sustainable growth, well‐being and retention in research ...
Timothy Lin Yun Tan +3 more
wiley +1 more source