Results 141 to 150 of about 376,109 (314)

Optimizing photoactivation of PA‐mCherry for optical pooled CRISPR screens

FEBS Open Bio, EarlyView.
Photoactivatable PA‐mCherry finds widespread use to optically tag individual cells. However, confocal 405 nm UV laser‐scanning (normal scan) is much less efficient than widefield UV illumination, limiting the use of PA‐mCherry on confocal instruments. We remedy this limitation by reporting that rapid and repeated confocal scanning with a low‐intensity,
Sravasti Mukherjee, Giulia Zanetti, Bram van den Broek, Kees Jalink   +3 more
wiley   +1 more source

Effective Scenarios in Distributionally Robust Optimization

, 2018
Traditional stochastic optimization assumes that the probability distribution of uncertainty is known. However, in practice, the probability distribution oftentimes is not known or cannot be accurately approximated. One way to address such distributional
Bayraksan, Guzin
core  

Towards fair class-wise robustness: class optimal distribution adversarial training

Complex & Intelligent Systems
Adversarial training has proven to be a highly effective method for improving the robustness of deep neural networks against adversarial attacks. Nonetheless, it has been observed to exhibit a limitation in terms of robust fairness, characterized by a ...
Hongxin Zhi, Hongtao Yu, Shaomei Li, Xiuming Zhao, Yiteng wu   +4 more
doaj   +1 more source

Refinement of amino‐acid conformation vs. difference density maps in time‐resolved serial femtosecond crystallography data analysis

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, Yuhei Hosokawa, Lars Oliver Essen, Manuel Maestre‐Reyna   +3 more
wiley   +1 more source

From Data to Decisions: Distributionally Robust Optimization is Optimal

, 2018
Data-driven stochastic programming aims to find a procedure that transforms time series data to a near-optimal decision (a prescriptor) and to a prediction of this decision's expected cost under the unknown data-generating distribution (a predictor).
Kuhn, Daniel
core  

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, Christine Volmert, Valentina Piano   +2 more
wiley   +1 more source

Measuring the Value of Randomized Solutions in Distributionally Robust Optimization

, 2018
This talk studies the value of randomized solutions (VRS) in distributionally robust mixed integer programming problems. We show different methods for obtaining upper bounds on VRS and identify conditions under which some of them are tight.
Delage, Erick
core  

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Distributionally Robust Optimization with Principal Component Analysis

, 2019
In this talk, we propose a new approximation method to solve distributionally robust optimization problems with moment-based ambiguity sets.
Cheng, JianQiang
core  

Hyperosmotic stress‐induced redistribution of pre‐mRNA cleavage factor I subunits is associated with shifts in alternative polyadenylation

FEBS Open Bio, EarlyView.
Hyperosmotic stress triggers the relocation of the CFIm complex from the nucleus to the cytoplasm. This shift creates a nuclear ‘stoichiometric bottleneck’, limiting CFIm availability for mRNA processing. Consequently, specific mRNAs like NUDT21 and DICER1 undergo targeted 3′UTR shortening, demonstrating how spatial protein dynamics drive rapid ...
Hitomi Soumiya, Masatake Osawa, Hidefumi Fukumitsu   +2 more
wiley   +1 more source