RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells
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
Estimating treatment effectiveness with sample selection [PDF]
We consider a situation where treatment outcome is observed after two stages of selection; first of participation into the treatment, then in completion of the treatment. Estimates were obtained using two methods.
Vidhura Tennekoon +3 more
core
Automating parameter selection to avoid implausible biological pathway models. [PDF]
Magnano CS, Gitter A.
europepmc +1 more source
Time‐restricted feeding (TRF) in mice increased liver fatty acid oxidation and decreased fatty acid biosynthesis. These alterations persisted when TRF was discontinued and the host was infected with Mycobacterium tuberculosis. Pre‐exposure to TRF did not alter tissue (lung and spleen) mycobacterial burden but significantly reduced CD3+ T cells in lungs
Ashish Gupta +7 more
wiley +1 more source
Bandwidth selection for nonparametric kernel testing [PDF]
We propose a sound approach to bandwidth selection in nonparametric kernel testing. The main idea is to find an Edgeworth expansion of the asymptotic distribution of the test concerned.
Gao, Jiti, Gijbels, Irene
core +1 more source
Deformable image registration accuracy: impact of user-defined parameter selection on contour propagation for deep inspiration breath-hold and free breathing breast radiotherapy. [PDF]
Knippen S +5 more
europepmc +1 more source
Automated Parameter Selection for Accelerated MRI Reconstruction via Low-Rank Modeling of Local k-Space Neighborhoods. [PDF]
Ilicak E, Saritas EU, Çukur T.
europepmc +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
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 +2 more
wiley +1 more source
Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old. [PDF]
Lee KS, Ham BJ.
europepmc +2 more sources
The Interphase Gap Effect in Cochlear Implant Users: Biological Basis, Parameter Selection, Analytical Methods, and Quantitative Scales. [PDF]
He S, Gao Z, Oleson JJ, Bruce IC.
europepmc +1 more source

