Showing papers in "Methods in 2022"

TL;DR: In this paper , the main properties, applications, and synthesis methods of magnetite, together with the newest advancements in this field are presented, as well as a review of the main applications, applications and methods for magnetite.

TL;DR: In this paper , a novel model based on transformer architecture and deep learning to identify DNA 6 mA sites from the cross-species genome was presented, which achieved excellent performance during independent test with the accuracy and Matthews correlation coefficient (MCC) of 79.3% and 0.58% respectively.

TL;DR: In this paper , a facile, inexpensive, and eco-friendly approach for green synthesis of ZnO-reduced graphene oxide nanocomposites using garlic clove extract was reported.

TL;DR: A review on CRISPR-based technologies and their perspectives to become platforms for point-of-care nucleic acid detection methods and as deployable diagnostic platforms that could help to identify and curb outbreaks and emerging epidemics is presented in this paper .

TL;DR: Zhang et al. as discussed by the authors proposed a hierarchical framework based on two-dimensional superpixels and deep learning to improve the existing accuracy of skin cancer diagnosis, which achieved an accuracy of 95.40%, 91.1%, and 85.50%, respectively.

TL;DR: DeepFusion as discussed by the authors is a deep learning based multi-scale feature fusion method for predicting drug-target interactions (DTIs) for both drug discovery and drug repositioning.

TL;DR: In this article , procedures involved in the thin-film hydration method, a commonly used method for the preparation of niosomes, are described in detail, while highlighting precautions that should be considered for consistent and reproducible construction of Niosomes.

TL;DR: Wang et al. as mentioned in this paper focused on automatic Cholangiocarcinoma (CC) diagnosis from microscopic hyperspectral (HSI) pathological dataset with deep learning method.

TL;DR: In this paper , the authors discuss and present compilation of state-of-the-art detection techniques for COVID-19 using CRISPR technology which has tremendous potential to transform diagnostics and epidemiology.

TL;DR: In this article , a compact and interpretable Convolutional Neural Network (CNN) was proposed to discover shared EEG features across different subjects for driver drowsiness detection, which achieved an average accuracy of 73.22% on 11 subjects for 2-class cross-subject EEG signal classification, which is higher than conventional machine learning methods and other state-of-theart deep learning methods.

TL;DR: In this paper , the authors present potential mechanisms by which advanced glycation end products (AGEs) cause or exacerbate musculoskeletal disorders, such as osteoporosis, osteoarthritis, sarcopenia, tendinopathy, and neuropathy.

TL;DR: In this article , the authors provide a review of the current methods for developing polymeric nanocapsules, reporting aspects to be considered when choosing appropriate materials, and discussing different ways to produce polymeric nanoparticles for superior performances.

TL;DR: The NodeIdentifyR algorithm (NIRA) as mentioned in this paper was proposed to identify the projected most efficient, symptom-specific intervention target in a network model (i.e., the Ising model).

TL;DR: Wang et al. as discussed by the authors developed a deep learning-based model to predict 4mC sites in the Escherichia coli genome using word embedding technique 'word2vec'.

TL;DR: Based on hybrid features and a random forest, a novel predictor, RFhy-m2G, was developed to identify the n2-methylguanosine modification sites for three species as mentioned in this paper .

TL;DR: In this article , a panel of reverse transcription droplet digital PCR (RT-ddPCR) assays was designed to specifically quantify multiple different subgenomic SARS-CoV-2 transcripts and distinguish them from transcripts that do not arise from discontinuous transcription at each locus.

TL;DR: In this paper , a federated learning framework for real-time emotion state classification using multi-modal physiological data streams from wearable sensors, called Fed-ReMECS, was developed.

TL;DR: In this article , the authors identify potential drugs using an in-silico approach and molecular docking was carried out on both approved drugs and substances previously tested in vivo, followed by a more detailed analysis of selected ligands by molecular dynamics simulations to identify the best molecules that thwart the ability of the virus to interact with the ACE2 receptor.

TL;DR: In this paper , the procedures involved in emulsification-solvent evaporation method, one of the commonly utilized methods for preparation of NLCs, are described in detail.

TL;DR: In this article , a multi-channel multi-scale deep neural network (DNN) model is proposed, which is an end-to-end structure to classify the ECG signals without any feature extraction.

TL;DR: In this article , the authors discuss the application of top-down and middle-down mass spectrometry (MS) in the study of protein deamidation, including sample preparation methods, separation strategies, MS and MS/MS techniques and data analysis.

TL;DR: In this article , a simple but efficient subject matching framework was proposed by finding a connection between a target (test) subject and source (training) subjects, which includes two stages: (1) training the model with multi-source domain alignment layers to collect source domain statistics; (2) during testing, a distance is computed to perform subject matching in the latent representation space.

TL;DR: Zhang et al. as mentioned in this paper proposed a computational model based on multiple descriptors and feature selection to jointly express samples to distinguish between strong and weak promoters, which achieved a sensitivity of 85.72% and accuracy of 77.00%.

TL;DR: In this article , the authors mainly focus on the Cas12-based methods and briefly discuss their applications in nucleic acids detection and beyond, and discuss their potential applications in DNA sequencing and beyond.

TL;DR: Peng et al. as mentioned in this paper proposed a tool called Penguin that integrates several machine learning (ML) models to identify RNA Pseudouridine sites on Nanopore direct RNA sequencing reads.

TL;DR: The AGE Reader has been developed to assess skin autofluorescence (SAF) non-invasively using the fluorescent properties of several advanced glycation endproducts (AGEs) as mentioned in this paper .

TL;DR: In this article , a review highlights various synthetic approaches to prepare disulfide containing redox-responsive polymeric nanomedicine, including synthesis of disulfides containing polymers, construction of polymeric nanoparticle with shell or core cross-linked dis-ulfide bonds, preparation of polymer-drug conjugates via disulide linkers, and disulfided linked responsive payloads.

TL;DR: In this article , the authors comprehensively explore machine learning based approaches for predicting 10 types of methylation of RNA, which include m6A, m5C, m7G, 5hmC and m1A,m5U, m6Am, and so on.

TL;DR: In this article , an in-silico Human-nCoV network was developed by identifying potential COVID-19 human spreader proteins by applying the SIS model and fuzzy thresholding by a possible COVID19 FDA drugs target-based validation.

TL;DR: A comprehensive review of the intrinsic disorder prediction field can be found in this paper , where the authors highlight accurate and popular intrinsic disorder predictors and introduce a wide range of practical resources that support collection, interpretation and application of disorder predictions.