Results 41 to 50 of about 193,490 (288)

AAA+ protein unfoldases—the Moirai of the proteome

open access: yesFEBS Letters, EarlyView.
AAA+ unfoldases are essential molecular motors that power protein degradation and disaggregation. This review integrates recent cryo‐electron microscopy (cryo‐EM) structures and single‐molecule biophysical data to reconcile competing models of substrate translocation.
Stavros Azinas, Marta Carroni
wiley   +1 more source

A General Combinatorial Ant System-based Distributed Routing Algorithm for Communication Networks [PDF]

open access: yesJournal of Systemics, Cybernetics and Informatics, 2007
In this paper, a general Combinatorial Ant System-based distributed routing algorithm modeled like a dynamic combinatorial optimization problem is presented.
Jose Aguilar, Miguel Labrador
doaj  

Potential therapeutic targeting of BKCa channels in glioblastoma treatment

open access: yesMolecular Oncology, EarlyView.
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak   +4 more
wiley   +1 more source

Computational Complexity and Phase Transitions

open access: yes, 2000
Phase transitions in combinatorial problems have recently been shown to be useful in locating "hard" instances of combinatorial problems. The connection between computational complexity and the existence of phase transitions has been addressed in ...
Istrate, Gabriel
core   +1 more source

Combinatorial Properties and Defragmentation Algorithms in WSW1 Switching Fabrics [PDF]

open access: yesInternational Journal of Electronics and Telecommunications, 2020
A spectrum defragmentation problem in elastic optical networks was considered under the assumption that all connections can be realized in switching nodes.
Remigiusz Rajewski   +2 more
doaj   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

open access: yesMolecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee   +8 more
wiley   +1 more source

The Consistency dimension and distribution-dependent learning from queries [PDF]

open access: yes, 2000
We prove a new combinatorial characterization of polynomial learnability from equivalence queries, and state some of its consequences relating the learnability of a class with the learnability via equivalence and membership queries of its subclasses ...
Balcázar Navarro, José Luis   +2 more
core   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns   +10 more
wiley   +1 more source

A Probabilistic Proof of the Multinomial Theorem

open access: yes, 2016
In this note, we give an alternate proof of the multinomial theorem using a probabilistic approach. Although the multinomial theorem is basically a combinatorial result, our proof may be simpler for a student familiar with only basic probability concepts.
Kataria, K. K.
core   +1 more source

Combinatorial probability and the tightness of generalization bounds [PDF]

open access: yesPattern Recognition and Image Analysis, 2008
Accurate prediction of the generalization ability of a learning algorithm is an important problem in computational learning theory. The classical Vapnik-Chervonenkis (VC) generalization bounds are too general and therefore overestimate the expected error. Recently obtained data-dependent bounds are still overestimated.
openaire   +1 more source

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