Studies of the human microbiome, and microbial community ecology in general, have blossomed of late and are now a burgeoning source of exciting research findings. Along with the advent of next-generation sequencing platforms, which have dramatically increased the scope of microbiome-related projects, several high-performance sequence analysis pipelines (e.g. QIIME, MOTHUR, VAMPS) are now available to investigators for microbiome analysis. The subject of our manuscript, the graphical user interface-based Explicet software package, fills a previously unmet need for a robust, yet intuitive means of integrating the outputs of the software pipelines with user-specified metadata and then visualizing the combined data.
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http://dx.doi.org/10.1093/bioinformatics/btt526 | DOI Listing |
Chemosphere
December 2024
Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ, 07030, USA. Electronic address:
Phosphate (PO(III)) contamination in water bodies poses significant environmental challenges, necessitating efficient and accurate methods to predict and optimize its removal. The current study addresses this issue by predicting the adsorption capacity of PO(III) ions onto biochar-based materials using five probabilistic machine learning models: eXtreme Gradient Boosting LSS (XGBoostLSS), Natural Gradient Boosting, Bayesian Neural Networks (NN), Probabilistic NN, and Monte-Carlo Dropout NN. Utilizing a dataset of 2952 data points with 16 inputs, XGBoostLSS demonstrated the highest R (0.
View Article and Find Full Text PDFJ Neurol Sci
December 2024
Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council (CTNLab-ISTC-CNR), Via Gian Domenico Romagnosi 18A, Rome 00196, Italy; AI2Life s.r.l., Innovative Start-Up, ISTC-CNR Spin-Off, Via Sebino 32, Rome 00199, Italy. Electronic address:
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasive, lacking consideration of sex-based differences. This study introduces an explainable machine learning (ML) system to predict and differentiate the progression of AD based on sex, using non-invasive, easily collectible predictors such as neuropsychological test scores and sociodemographic data, enabling its application in every day clinical settings.
View Article and Find Full Text PDFComput Methods Programs Biomed
December 2024
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Background And Objective: Dysfunction of the right ventricular outflow tract (RVOT) is a common long-term complication following surgical repair in patients with congenital heart disease. Transcatheter pulmonary valve implantation (TPVI) offers a viable alternative to surgical pulmonary valve replacement (SPVR) for treating pulmonary regurgitation but not all RVOT anatomies are suitable for TPVI. To identify a suitable landing zone (LZ) for TPVI, three-dimensional multiphase (4D) computed tomography (CT) is used to evaluate the size, shape, and dynamic behavior of the RVOT throughout the cardiac cycle.
View Article and Find Full Text PDFHealthc Technol Lett
December 2024
ITI/LARSyS, Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal.
A thorough understanding of surgical anatomy is essential for preparing and training medical students to become competent and skilled surgeons. While Virtual Reality (VR) has shown to be a suitable interaction paradigm for surgical training, traditional anatomical VR models often rely on simple labels and arrows pointing to relevant landmarks. Yet, studies have indicated that such visual settings could benefit from knowledge maps as such representations explicitly illustrate the conceptual connections between anatomical landmarks.
View Article and Find Full Text PDFPlant Methods
December 2024
Department of Molecular Genetics, Dong-A University, Saha-gu Nakdong-Daero 550 beongil 37, Busan, 49315, Republic of Korea.
Background: Genetic markers are crucial for breeding crops with desired agronomic traits, and their development can be expedited using next-generation sequencing (NGS) and bioinformatics tools. Numerous tools have been developed to design molecular markers, enhancing the convenience, accuracy, and efficiency of molecular breeding. However, these tools primarily focus on genetic variants within short user-input sequences, despite the availability of extensive omics data for genomic variants.
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