Results 51 to 60 of about 640,433 (264)
Tumor mutational burden as a determinant of metastatic dissemination patterns
Molecular Oncology, EarlyView.This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal +4 more
wiley +1 more source
Hierarchical Reinforcement Learning: A Survey and Open Research Challenges
Machine Learning and Knowledge Extraction, 2022 Reinforcement learning (RL) allows an agent to solve sequential decision-making problems by interacting with an environment in a trial-and-error fashion. When these environments are very complex, pure random exploration of possible solutions often fails,
Matthias Hutsebaut-Buysse +2 more
doaj +1 more source
Combining Hebbian and reinforcement learning in a minibrain model
, 2003 A toy model of a neural network in which both Hebbian learning and reinforcement learning occur is studied. The problem of `path interference', which makes that the neural net quickly forgets previously learned input-output relations is tackled by adding
Bosman, R. J. C. +2 more
core +1 more source
Overview of molecular signatures of senescence and associated resources: pros and cons
FEBS Open Bio, EarlyView.Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas +6 more
wiley +1 more source
Digital twins to accelerate target identification and drug development for immune‐mediated disorders
FEBS Open Bio, EarlyView.Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley +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
Safe Model-Based Reinforcement Learning for Systems With Parametric Uncertainties
Frontiers in Robotics and AI, 2021 Reinforcement learning has been established over the past decade as an effective tool to find optimal control policies for dynamical systems, with recent focus on approaches that guarantee safety during the learning and/or execution phases.
S. M. Nahid Mahmud +3 more
doaj +1 more source
Distributional Reinforcement Learning with Quantile Regression
, 2017 In reinforcement learning an agent interacts with the environment by taking actions and observing the next state and reward. When sampled probabilistically, these state transitions, rewards, and actions can all induce randomness in the observed long-term
Bellemare, Marc G. +3 more
core +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
Efficient Hindsight Experience Replay with Transformed Data Augmentation
Journal of Applied Science and Engineering, 2023 Motion control of robots is a high-dimensional, nonlinear control problem that is often difficult to handle using traditional dynamical path planning means.
Jiazheng Sun, Weiguang Li
doaj +1 more source