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http://dx.doi.org/10.1113/JP276501 | DOI Listing |
Bioinformatics
January 2025
School of Artificial Intelligence, Jilin University, Jilin, China.
Motivation: Predicting RNA-binding proteins (RBPs) is central to understanding post-transcriptional regulatory mechanisms. Here, we introduce EnrichRBP, an automated and interpretable computational platform specifically designed for the comprehensive analysis of RBP interactions with RNA.
Results: EnrichRBP is a web service that enables researchers to develop original deep learning and machine learning architectures to explore the complex dynamics of RNA-binding proteins.
Invest Ophthalmol Vis Sci
January 2025
Southwest Hospital/Southwest Eye Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Purpose: Previous studies have reported divergent sexual responses to aging; however, specific variations in gene expression between aging males and females and their potential association with age-related retinal diseases remain unclear. This study collected data from public databases and developed a comprehensive comparison of retina between aging females and males.
Methods: Single-cell RNA (scRNA) and bulk RNA sequencing data of the aging retina from females and males in public databases were utilized for integrated analysis to investigate sex-biased expression in retina.
J Vis
January 2025
Neural Information Processing Group, University of Tübingen, Tübingen, Germany.
Human performance in psychophysical detection and discrimination tasks is limited by inner noise. It is unclear to what extent this inner noise arises from early noise (e.g.
View Article and Find Full Text PDFActa Crystallogr F Struct Biol Commun
February 2025
Institute for Biochemistry and Biology, University of Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany.
Screening of cryo-EM samples is essential for the generation of high-resolution cryo-EM structures. Often, it is cumbersome to correlate the appearance of specific grid squares and micrograph quality. Here, CryoCrane (Correlate atlas and exposures), a visualization tool for cryo-EM screening data, is presented.
View Article and Find Full Text PDFInsights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
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