Results 71 to 80 of about 862,801 (304)
Molecular Oncology, EarlyView.In luminal (ER+) breast carcinoma (BC), miRNA profiling identified miR‐195‐5p as a key regulator of proliferation that targets CHEK1, CDC25A, and CCNE1. High CHEK1 expression correlates with worse relapse‐free survival after chemotherapy, especially in patients with luminal A subtype.
Veronika Boušková +14 more
wiley +1 more source
Performance of NOMA-Based mmWave D2D Networks Under Practical System Conditions
IEEE Access, 2021 This work elaborates the analysis on ergodic capacity, coverage probability, and average throughput for multi-user non-orthogonal multiple access (NOMA) based device-to-device communication networks, which operate in the millimeter-wave spectrum range ...
Leila Tlebaldiyeva +3 more
doaj +1 more source
Molecular Oncology, EarlyView.Proteomic and phosphoproteomic analyses were performed on lung adenocarcinoma (LUAD) tumors with EGFR, KRAS, or EML4–ALK alterations and wild‐type cases. Distinct protein expression and phosphorylation patterns were identified, especially in EGFR‐mutated tumors. Key altered pathways included vesicle transport and RNA splicing.
Fanni Bugyi +12 more
wiley +1 more source
Decrypting cancer's spatial code: from single cells to tissue niches
Molecular Oncology, EarlyView.Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik +4 more
wiley +1 more source
IEEE Access, 2016 The device-to-device (D2D) communication has been regarded as an effective technique for complementing and enhancing the conventional cellular systems owing to its capability of substantially improving both the spectral and power efficiencies of wireless
Jian Sun +6 more
doaj +1 more source
Neural network probability estimation for broad coverage parsing [PDF]
Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - EACL '03, 2003 We present a neural-network-based statistical parser, trained and tested on the Penn Treebank. The neural network is used to estimate the parameters of a generative model of left-corner parsing, and these parameters are used to search for the most probable parse.
openaire +3 more sources
Finite random coverings of one-complexes and the Euler characteristic
, 2014 This article presents an algebraic topology perspective on the problem of finding a complete coverage probability of a one dimensional domain $X$ by a random covering, and develops techniques applicable to the problem beyond the one dimensional case.
Komendarczyk, Rafal, Pullen, Jeffrey
core +1 more source
Molecular Oncology, EarlyView.This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan +9 more
wiley +1 more source
A Penalized Likelihood Approach to Parameter Estimation with Integral Reliability Constraints
Entropy, 2015 Stress-strength reliability problems arise frequently in applied statistics and related fields. Often they involve two independent and possibly small samples of measurements on strength and breakdown pressures (stress).
Barry Smith +3 more
doaj +1 more source
Explicit nonparametric confidence intervals for the variance with guaranteed coverage [PDF]
, 2001 In this paper, we provide a method for constructing confidence intervals for the variance that exhibit guaranteed coverage probability for any sample size, uniformly over a wide class of probability distributions.
Romano, Joseph P., Wolf, Michael
core +1 more source