Results 41 to 50 of about 11,198,718 (212)

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

Complexity Framework for Forbidden Subgraphs IV: The Steiner Forest Problem [PDF]

, 2023
We study Steiner Forest on H-subgraph-free graphs, that is, graphs that do not contain some fixed graph H as a (not necessarily induced) subgraph. We are motivated by a recent framework that completely characterizes the complexity of many problems on H ...
Oostveen, Jelle, van Leeuwen, Erik Jan, Johnson, Matthew, Smith, Siani, Bodlaender, Hans L., Pandey, Sukanya, Paulusma, Daniël, Martin, Barnaby   +7 more
core  

ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks

Journal of Statistical Software, 2018
Stochastic simulation and modeling play an important role to elucidate the fundamental mechanisms in complex biochemical networks. The parametric sensitivity analysis of reaction networks becomes a powerful mathematical and computational tool, yielding ...
Weilong Hu, Yannis Pantazis, Markos A. Katsoulakis   +2 more
doaj   +1 more source

Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang, Dongxu Zhang, Dongyuan Liu, Da Lin, Hao Wang   +4 more
wiley   +1 more source

On Invertibility of Large Binary Matrices

Mathematics
Many data processing applications involve binary matrices for storing digital information. At present, there are limited results in the literature about algorithms for inverting large binary matrices.
Ibrahim Mammadov, Pavel Loskot, Thomas Honold   +2 more
doaj   +1 more source

Algorithms for effective querying of compound graph-based pathway databases

BMC Bioinformatics, 2009
Background Graph-based pathway ontologies and databases are widely used to represent data about cellular processes. This representation makes it possible to programmatically integrate cellular networks and to investigate them using the well-understood ...
Demir Emek, Cetintas Ahmet, Dogrusoz Ugur, Babur Ozgun   +3 more
doaj   +1 more source

Low-degree learning and the metric entropy of polynomials

Discrete Analysis, 2023
Low-degree learning and the metric entropy of polynomials, Discrete Analysis 2023:17, 23 pp. This paper is a follow-up to a paper by the first two authors on the general problem of designing algorithms that can efficiently learn functions defined on ...
Alexandros Eskenazis, Paata Ivanisvili, Lauritz Streck   +2 more
doaj   +1 more source

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

Algorithms and Bounds for Very Strong Rainbow Coloring [PDF]

, 2018
A well-studied coloring problem is to assign colors to the edges of a graph G so that, for every pair of vertices, all edges of at least one shortest path between them receive different colors. The minimum number of colors necessary in such a coloring is
van Leeuwen, E., Chandran, Sunil L, Das, A., van Leeuwen, Erik Jan, Mosteiro, Miguel A., Chandran, L. Sunil, Chandran, L., Bender, Michael A., Farach-Colton, Martin, Issac, D., Erik Jan van Leeuwen, Leeuwen, Erik Jan van, Davis Issac, Das, Anita, Anita Das, Issac, Davis, Sub Algorithms and Complexity, L. Sunil Chandran, Algorithms and Complexity   +18 more
core   +2 more sources

CSF Cytokine Network Organization Predicts Progression Independent of Relapse and MRI Activity in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progression independent of relapse activity is a major determinant of long‐term disability in multiple sclerosis, but its immunopathologic basis remains incompletely understood. We investigated whether relapse‐independent progression in radiologically stable relapsing–remitting multiple sclerosis is associated with distinct ...
Antonio Bruno, Matteo Conti, Ettore Dolcetti, Federica Azzolini, Angela Borrelli, Roberta Fantozzi, Mario Stampanoni Bassi, Giovanni Galifi, Giuseppe Maccarrone, Luca Montaguti, Marco Cervigni, Maddalena Dal Pozzo, Roberto Furlan, Annamaria Finardi, Girolama Alessandra Marfia, Marco Salvetti, Antonella Conte, Fabio Buttari, Diego Centonze, Luana Gilio   +19 more
wiley   +1 more source