Results 121 to 130 of about 376,109 (314)
FEBS Open Bio, EarlyView.RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
TGersing/robust-binary-optimization
<p>Improved the performance of the BnB by adding new features as described in the thesis "Algorithms for Robust Combinatorial Optimization with Budgeted Uncertainty and Fair Planning of the Out-of-Hours Service for Pharmacies". Also added
TGersing
core +1 more source
Approximated computation of belief functions for robust design optimization
, 2012 This paper presents some ideas to reduce the computational cost of evidence-based robust design optimization. Evidence Theory crystallizes both the aleatory and epistemic uncertainties in the design parameters, providing two quantitative measures, Belief
Massimilano Vasile +5 more
core +1 more source
Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies
FEBS Open Bio, EarlyView.We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli +8 more
wiley +1 more source
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
Robust Solutions of Optimization Problems Affected by Uncertain Probabilities
In this paper we focus on robust linear optimization problems with uncertainty regions defined by ø-divergences (for example, chi-squared, Hellinger, Kullback-Leibler).
De Waegenaere, A.M.B. +4 more
core
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
Distributionally Robust Chance Constrained Geometric Optimization
, 2018 In this talk, we discuss distributionally robust geometric programs with individual and joint chance constraints. We consider three groups of uncertainty sets, namely uncertainty sets with known two first order moments information, uncertainty sets ...
Lisser, Abdel
core
Systemic dysregulation of apolipoproteins in amyotrophic lateral sclerosis serum
FEBS Open Bio, EarlyView.Amyotrophic lateral sclerosis (ALS) is a fatal disease that damages motor neurons. This study found that people with ALS show significant changes in blood fats and the proteins that carry them. Several apolipoproteins were higher, lipid balances were altered, and normal protein–lipid relationships were disrupted.
Finula I. Isik +6 more
wiley +1 more source
Distributionally Robust Stochastic and Online Optimization
, 2019 We present decision/optimization models/problems driven by uncertain and online data, and show how analytical models and computational algorithms can be used to achieve solution efficiency and near optimality.
Ye, Yinyu
core