Results 101 to 110 of about 571,192 (299)

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu   +10 more
wiley   +1 more source

Cracking the Code: Genotype–Phenotype Correlation Models in Sarcoglycanopathies

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Sarcoglycanopathies are among the most severe limb‐girdle muscular dystrophies (LGMD), though milder presentations have been described. These diseases are primarily caused by missense variants, but the limited predictability of their effect on protein maturation, complex formation, and transport has hindered reliable genotype ...
Leonela Luce   +72 more
wiley   +1 more source

Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads. [PDF]

open access: yes, 2019
As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples.
Arthur, Timothy D   +30 more
core   +1 more source

A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento   +3 more
wiley   +1 more source

Understanding the liver under heat stress with statistical learning: an integrated metabolomics and transcriptomics computational approach

open access: yesBMC Genomics, 2019
Background We present results from a computational analysis developed to integrate transcriptome and metabolomic data in order to explore the heat stress response in the liver of the modern broiler chicken.
Allen H. Hubbard   +4 more
doaj   +1 more source

Improving nanopore read accuracy with the R2C2 method enables the sequencing of highly multiplexed full-length single-cell cDNA. [PDF]

open access: yes, 2018
High-throughput short-read sequencing has revolutionized how transcriptomes are quantified and annotated. However, while Illumina short-read sequencers can be used to analyze entire transcriptomes down to the level of individual splicing events with ...
Byrne, Ashley   +6 more
core   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical applications, challenges, and future directions

open access: yesArthritis Care &Research, Accepted Article.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Aptamer selection by high-throughput sequencing and informatic analysis

open access: yesBioTechniques, 2011
Traditional methods for selecting aptamers require multiple rounds of selection and optimization in order to identify aptamers that bind with high affinity to their targets.
Shawn Hoon   +4 more
doaj   +1 more source

ParMap, an Algorithm for the Identification of Complex Genomic Variations in Nextgen Sequencing Data [PDF]

open access: yes, 2010
Next-generation sequencing produces high-throughput data, albeit with greater error and shorter reads than traditional Sanger sequencing methods. This complicates the detection of genomic variations, especially, small insertions and deletions.
Adolfo A. Ferrando   +4 more
core   +1 more source

What Do Large Language Models Know About Materials?

open access: yesAdvanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer   +2 more
wiley   +1 more source

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