Results 111 to 120 of about 3,472,659 (303)
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
FEBS Letters, EarlyView.Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source
Introduction to the Special Issue on Mixture Structural Equation Modeling
, 2006 Reinecke J. Introduction to the Special Issue on Mixture Structural Equation Modeling. Methodology.
Reinecke, Jost
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Mixture of Experts Classification Using a Hierarchical Mixture Model
Neural Computation, 2002 A three-level hierarchical mixture model for classification is presented that models the following data generation process: (1) the data are generated by a finite number of sources (clusters), and (2) the generation mechanism of each source assumes the existence of individual internal class-labeled sources (subclusters of the external cluster).
Titsias, M. K., Likas, A.
openaire +5 more sources
Liver organoids: modelling complexity in homeostasis and disease
FEBS Letters, EarlyView.Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
wiley +1 more source
An Introduction to Latent Variable Mixture Modeling (Part 2): Longitudinal Latent Class Growth Analysis and Growth Mixture Models [PDF]
, 2013 Objective — Pediatric psychologists are often interested in finding patterns in heterogeneous longitudinal data. Latent Variable Mixture Modeling is an emerging statistical approach that models such heterogeneity by classifying individuals into ...
Berlin, Kristoffer S. +2 more
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, 2019 This dataset contains the data for the article: Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection.
Osei, Dr. F. B. (Faculty of Geo-Information Science and Earth Observation (ITC) University of Twente), Researcher +1 more
core +1 more source
Bayesian mixture labeling and clustering [PDF]
, 2012 Label switching is one of the fundamental issues for Bayesian mixture modeling. It occurs due to the nonidentifiability of the components under symmetric priors. Without solving the label switching, the ergodic averages of component specific quantities
Yao, Weixin
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Using Mplus to detect careless responses with the help of a simple-to-use online application
Journal of Pacific Rim PsychologyCareless responding poses a notable challenge in measurement due to its potential to distort relationships between items. Factor mixture modeling, as a statistical modeling tool adept at identifying heterogeneous clusters within a population, has emerged
Shaobo Liang +2 more
doaj +1 more source
FEBS Letters, EarlyView.This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
Understanding the shape of the mixture failure rate (with engineering and demographic applications) [PDF]
Mixtures of distributions are usually effectively used for modeling heterogeneity. It is well known that mixtures of DFR distributions are always DFR. On the other hand, mixtures of IFR distributions can decrease, at least in some intervals of time.
Maxim S. Finkelstein
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