Results 91 to 100 of about 52,296 (256)

Signed Graph Unlearning

open access: yesICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
The proliferation of signed networks in contemporary social media platforms necessitates robust privacy-preserving mechanisms. Graph unlearning, which aims to eliminate the influence of specific data points from trained models without full retraining, becomes particularly critical in these scenarios where user interactions are sensitive and dynamic ...
Zhifei Luo   +3 more
openaire   +2 more sources

Interferon beta drives therapy resistance in a patient‐derived model of high‐grade serous ovarian cancer

open access: yesMolecular Oncology, EarlyView.
Interferon type 1 (IFN‐1) production and signaling is associated with the acquisition of therapy resistance, following chronic DNA damage, via Interferon‐related DNA damage resistance signature (IRDS) gene expression. An alternative, DNA damage‐independent role of sustained IFN‐1 mediated resistance was identified and characterized by the emergence of ...
Ashlyn Conant   +11 more
wiley   +1 more source

Whole-Graph Representation Learning for the Classification of Signed Networks

open access: yesIEEE Access
Graphs are ubiquitous for modeling complex systems involving structured data and relationships. Consequently, graph representation learning, which aims to automatically learn low-dimensional representations of graphs, has drawn a lot of attention in ...
Noe Cecillon   +3 more
doaj   +1 more source

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

open access: yesFEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei   +3 more
wiley   +1 more source

Identifying gene expression signatures for risk stratification of postoperative adjuvant chemotherapy in colorectal cancer

open access: yesFEBS Open Bio, EarlyView.
A novel signature integrating genome‐wide analysis with clinical factors predicts recurrence in stage II colorectal cancer and enables a new risk stratification to guide postoperative adjuvant chemotherapy. Clinical risk stratification for postoperative recurrence in patients with pathological stage II (pStage II) colorectal cancer (CRC) is essential ...
Mayuko Otomo   +7 more
wiley   +1 more source

An upper bound for the Laplacian index of a signed graph [PDF]

open access: yesDiscrete Mathematics Letters, 2021
Farzaneh Ramezani, Zoran Stanic
doaj   +1 more source

MagmaFlow: A desktop platform for artificial intelligence‐driven expression analysis

open access: yesFEBS Open Bio, EarlyView.
MagmaFlow is a free, no‐code platform for gene expression analysis. It generates interactive volcano plots, links genes to literature, pathways, and diseases, prioritizes candidates using millions of publications, identifies affected biological processes, builds network diagrams, and exports publication‐ready figures and reports for macOS and Windows ...
Carlos E. Buss   +7 more
wiley   +1 more source

Edge coloring of small signed graphs

open access: yesTASK Quarterly
In 2020, Behr introduced the problem of edge coloring of signed graphs and proved that every signed graph (G, sigma) can be colored using Delta(G) or Delta(G) + 1 colors, where Delta(G) denotes the maximum degree of G.
Robert Janczewski   +2 more
doaj  

Computing the determinant of a signed graph

open access: yesOpen Mathematics
A signed graph is a simple graph in which every edge has a positive or negative sign. In this article, we employ several algebraic techniques to compute the determinant of a signed graph in terms of the spectrum of a vertex-deleted subgraph.
Alshamary Bader, Stanić Zoran
doaj   +1 more source

Kernelized multiview signed graph learning for single-cell RNA sequencing data. [PDF]

open access: yesBMC Bioinformatics, 2023
Karaaslanli A   +3 more
europepmc   +1 more source

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