Results 111 to 120 of about 4,220,209 (306)
Molecular Oncology, EarlyView.Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur +11 more
wiley +1 more source
A Maximum Likelihood Approach to Estimation of Heath-Jarrow-Morton Models [PDF]
Research on the Heath-Jarrow-Morton (1992) term structure models so far has focused on the class having time-deterministic instantaneous forward rate volatility. In this case the forward rate is Markovian, even if the spot rate process is not.
Ram Bhar, Carl Chiarella, Thuy Duong To
core
Molecular Oncology, EarlyView.Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq +8 more
wiley +1 more source
Indirect likelihood inference [PDF]
Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of
Michael Creel, Dennis Kristensen
core
Molecular Oncology, EarlyView.Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park +6 more
wiley +1 more source
logcondens: Computations Related to Univariate Log-Concave Density Estimation [PDF]
Maximum likelihood estimation of a log-concave density has attracted considerable attention over the last few years. Several algorithms have been proposed to estimate such a density. Two of those algorithms, an iterative convex minorant and an active set
Lutz Dümbgen, Kaspar Rufibach
core
Likelihood inference for small variance components
, 2000 In this paper, we develop likelihood-based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, we use local asymptotic approximations to construct confidence intervals for the components ...
Stern, S.E., Welsh, A.H.
core +1 more source
Cancer‐associated mutations in endometriosis reframe a benign disease through molecular oncology
Molecular Oncology, EarlyView.This review aims to comprehensively analyse cancer‐associated somatic mutations (CAMs) present in endometriotic lesions, emphasizing their biological roles, spatial distribution and implications for translational applications in medicine. By contextualizing a benign state within a genomic framework, this analysis seeks to establish its value as a ...
Clarissa Mujacic +15 more
wiley +1 more source
Parameter Estimation in Semi-Linear Models Using a Maximal Invariant Likelihood Function [PDF]
In this paper, we consider the problem of estimation of semi-linear regression models. Using invariance arguments, Bhowmik and King (2001) have derived the probability density functions of the maximal invariant statistic for the nonlinear component of ...
Jahar L. Bhowmik, Maxwell L. King
core
PANoptosis in the pathogenesis of myelodysplastic syndromes
Molecular Oncology, EarlyView.PANoptosis, a combination of three types of programmed cell death, is mediated by a large protein complex called a PANoptosome. In healthy bone marrow hematopoietic cells, PANoptosis is restricted by inhibitory signaling. In MDS, bone marrow cells become sensitive to the PANoptotic stimuli due to the aberrant inactivation of inhibitory signaling or ...
Rohit Thalla +4 more
wiley +1 more source