Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Nonlinear conjugate gradient method [PDF]
, 2019 V této práci studujeme nelineární metody sdružených gradientů pro nepodmíněnou optimalizaci. Uvádíme možnosti a limity stávajících metod nepodmíněné optimalizace.
Aleksandr Efremov
core
A New Smoothing Conjugate Gradient Method for Solving Nonlinear Nonsmooth Complementarity Problems
Algorithms, 2015 In this paper, by using the smoothing Fischer-Burmeister function, we present a new smoothing conjugate gradient method for solving the nonlinear nonsmooth complementarity problems.
Ajie Chu, Shouqiang Du, Yixiao Su
doaj +1 more source
A New sufficient descent Conjugate Gradient Method for Nonlinear Optimization [PDF]
المجلة العراقية للعلوم الاحصائية, 2014 In this paper, a new conjugate gradient method based on exact step size which produces sufficient descent search direction at every iteration is introduced. We prove its global convergence, and give some results to illustrate its efficiency by comparing
Dr. Basim A. Hassan, Omer M. Esmaeel
doaj +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
A Novel hybridization of CG-techniques for Solving Unconstrained Optimization Problems
Wasit Journal for Pure SciencesConjugate gradient methods are an extremely helpful way for handling large scale non-linear optimization issues. In this paper, based on the three famous Dai-yuan (DY), Liu–Storey (LS)and Conjugate-Descent (CD) conjugate gradient methods, a new hybrid ...
Hawraz Jabbar
doaj +1 more source
Dai-Kou type conjugate gradient methods with a line search only using gradient
Journal of Inequalities and Applications, 2017 In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope.
Yuanyuan Huang, Changhe Liu
doaj +1 more source
Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions
FEBS Letters, EarlyView.The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang +4 more
wiley +1 more source
Stability Analysis Of Continuous Conjugate Gradient Method [PDF]
, 2008 Kaedah Conjugate Gradient adalah sangat berguna untuk: menyelesaikan masalah tiada kekangan paling optimum yang berskala besar. Walaubagaimanapun, carlan garis (line search) dalam Kaedah Conjugate Gradient kadang-kadang sukar didapati dan pengiraannya
Harun, Nurzalina
core
A modified Fletcher-Reeves conjugate gradient method for unconstrained optimization with applications in image restoration [PDF]
summary:The Fletcher-Reeves (FR) method is widely recognized for its drawbacks, such as generating unfavorable directions and taking small steps, which can lead to subsequent poor directions and steps.
Hbaib, Mohamed +2 more
core +1 more source