Results 71 to 80 of about 114,130 (267)
Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
AlgorithmsInteger linear programs (ILPs) and mixed integer programs (MIPs) often have multiple distinct optimal solutions, yet the widely used Gurobi optimization solver returns certain solutions at disproportionately high frequencies.
Noah Schulhof +4 more
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Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
Machine Learning and Knowledge Extraction, 2020 Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem.
Joakim Linja +3 more
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FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
FEBS Open Bio, EarlyView.The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source
Randomized Estimation for Low-Light Imaging With Unknown-but-Bounded Noise
IEEE AccessThis paper addresses parameter estimation in low-light imaging when the number of observations is limited and the dominant uncertainty is unknown-but-bounded dark noise.
Konstantin Amelin +3 more
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Algorithms with greedy heuristic procedures for mixture probability distribution separation [PDF]
Yugoslav Journal of Operations Research, 2019 For clustering problems based on the model of mixture probability distribution separation, we propose new Variable Neighbourhood Search algorithms (VNS) and evolutionary genetic algorithms (GA) with greedy agglomerative heuristic procedures and compare ...
Kazakovtsev Lev +3 more
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Non-Algorithmic Theory of Randomness [PDF]
, 2020 This paper proposes an alternative language for expressing results of the algorithmic theory of randomness. The language is more precise in that it does not involve unspecified additive or multiplicative constants, making mathematical results, in principle, applicable in practice.
openaire +2 more sources
A yeast model of 5‐oxoproline accumulation reveals a general toleration to 5‐oxoproline
FEBS Open Bio, EarlyView.Using a yeast model, we show that even high accumulation of 5‐oxoproline causes only mild cellular stress and does not trigger oxidative stress. Instead, cells adapt by activating efflux pumps and diverse protective pathways, suggesting that previously proposed harmful effects of 5‐oxoproline may arise from indirect metabolic imbalances rather than the
Pratiksha Dubey +4 more
wiley +1 more source
RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells
FEBS Open Bio, EarlyView.RoundMi is a workflow for rapid analysis of mitochondrial morphology in mitotic cells. By combining adaptive preprocessing with automated segmentation and quantification, it enables accurate measurements from single focal plane images, reducing acquisition time and computational demands while remaining compatible with high‐throughput fixed and live ...
Elmira Parvindokht Bararpour +2 more
wiley +1 more source