Results 81 to 90 of about 5,051,769 (292)

Structural instability impairs function of the UDP‐xylose synthase 1 Ile181Asn variant associated with short‐stature genetic syndrome in humans

open access: yesFEBS Letters, EarlyView.
The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li   +2 more
wiley   +1 more source

Explicit Gaussian Variational Approximation for the Poisson Lognormal Mixed Model

open access: yesMathematics, 2022
In recent years, the Poisson lognormal mixed model has been frequently used in modeling count data because it can accommodate both the over-dispersion of the data and the existence of within-subject correlation.
Xiaoping Shi   +2 more
doaj   +1 more source

The human gut microbiome across the life course

open access: yesFEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero   +4 more
wiley   +1 more source

Speaker-dependent laser Doppler vibrometer–based voice conversion for dysarthric speech under noisy conditions [PDF]

open access: yesJASA Express Letters
This study proposed the integration of a laser Doppler vibrometer sensing with a Variational Inference with adversarial learning for Text-to-Speech–based voice conversion system to enhance automatic speech recognition for individuals with dysarthria in ...
Yu-Chuan Lee   +5 more
doaj   +1 more source

Iterative Amortized Inference [PDF]

open access: yes, 2018
Inference models are a key component in scaling variational inference to deep latent variable models, most notably as encoder networks in variational auto-encoders (VAEs).
Mandt, Stephan   +2 more
core   +2 more sources

Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra   +6 more
wiley   +1 more source

Symplectic encoders for physics-constrained variational dynamics inference

open access: yesScientific Reports, 2023
We propose a new variational autoencoder (VAE) with physical constraints capable of learning the dynamics of Multiple Degree of Freedom (MDOF) dynamic systems.
Kiran Bacsa   +4 more
doaj   +1 more source

Variational Inference in Nonconjugate Models

open access: yesJ. Mach. Learn. Res., 2012
Mean-field variational methods are widely used for approximate posterior inference in many probabilistic models. In a typical application, mean-field methods approximately compute the posterior with a coordinate-ascent optimization algorithm. When the model is conditionally conjugate, the coordinate updates are easily derived and in closed form ...
Chong Wang 0002, David M. Blei
openaire   +4 more sources

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

open access: yesMolecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson   +9 more
wiley   +1 more source

Message Passing-Based Inference for Time-Varying Autoregressive Models

open access: yesEntropy, 2021
Time-varying autoregressive (TVAR) models are widely used for modeling of non-stationary signals. Unfortunately, online joint adaptation of both states and parameters in these models remains a challenge.
Albert Podusenko   +2 more
doaj   +1 more source

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