A 3-D Chromosome Structure Reconstruction Method With High Resolution Hi-C Data Using Nonlinear Dimensionality Reduction and Divide-and-Conquer Strategy
In this study, we present NeRV-3D, an innovative method that utilizes a nonlinear dimensionality reduction visualization algorithm to reconstruct 3D chromosome structures at low resolutions. Additionally, we introduce NeRV-3D-DC, which employs a divide-and-conquer technique to reconstruct and visualize 3D chromosome structures at high resolutions. Our results demonstrate that both NeRV-3D and NeRV-3D-DC outperform existing methods in terms of 3D visualization effects and evaluation metrics on simulated and actual Hi-C datasets. The implementation of NeRV-3D-DC can be found at https://github.com/ghaiyan/ NeRV-3D-DC. (Source...
Source: IEE Transactions on NanoBioscience - May 18, 2023 Category: Nanotechnology Source Type: research
A Graph Convolution Network-Based Model for Prioritizing Personalized Cancer Driver Genes of Individual Patients
Cancer driver genes are mutated genes that play a key role in the growth of cancer cells. Accurately identifying the cancer driver genes helps us understand cancer’s pathogenesis and develop effective treatment strategies. However, cancers are highly heterogeneous diseases; patients with the same cancer type may have different genomic characteristics and clinical symptoms. Hence, it is urgent to devise effective methods to identify personalized cancer driver genes of individual patients to help determine whether a patient can be treated with a certain targeted drug. This work presents a method for predicting personalized...
Source: IEE Transactions on NanoBioscience - May 17, 2023 Category: Nanotechnology Source Type: research
Local Feature Matters: Cascade Multi-Scale MLP for Edge Segmentation of Medical Images
Convolution-based methods are increasingly being used in medical image segmentation tasks and have shown good performance, but there are always problems in segmenting edge parts. These methods all have the following challenges: 1) Previous methods do not highlight the relationship between foreground and background in segmented regions, which is helpful for complex segmentation edges, 2) inductive bias of the convolutional layer leads to the fact that the extracted information is mainly the main part of the segmented area, and cannot effectively perceive complex edge changes and the aggregation of small and many segmented a...
Source: IEE Transactions on NanoBioscience - May 15, 2023 Category: Nanotechnology Source Type: research
Extraction, Labeling, Clustering, and Semantic Mapping of Segments From Clinical Notes
This work is motivated by the scarcity of tools for accurate, unsupervised information extraction from unstructured clinical notes in computationally underrepresented languages, such as Czech. We introduce a stepping stone to a broad array of downstream tasks such as summarisation or integration of individual patient records, extraction of structured information for national cancer registry reporting or building of semi-structured semantic patient representations that can be used for computing patient embeddings. More specifically, we present a method for unsupervised extraction of semantically-labeled textual segments fro...
Source: IEE Transactions on NanoBioscience - May 11, 2023 Category: Nanotechnology Source Type: research
Predicting Plant miRNA-lncRNA Interactions via a Deep Learning Method
In recent years, due to the contribution to elucidating the functional mechanisms of miRNAs and lncRNAs, the research on miRNA-lncRNA interaction prediction has increased exponentially. However, the prediction research is challenging in bioinformatics domain. It is expensive and time-consuming to verify the interactions by biological experiments. The existing prediction models have some limitations, such as the need to manually extract features, the potential loss of features from pre-treatment approaches, long-distance dependency to be solved, and so on. Additionally, most of the current models prefer to the animal data. ...
Source: IEE Transactions on NanoBioscience - May 11, 2023 Category: Nanotechnology Source Type: research
A Biosensing Platform Based on Metamaterials BioNEMS for Lab-on-Chip Systems
An optical nanoelectromechanical platform relied on a SRR metamaterial system is presented in this paper as a label-free biosensor. This structure includes a flexible BioNEMS (Bio-Nano-Electro-Mechanical Systems) transducer and a proposed SRR metamaterials for detection of biological changes. Metamaterial cells consist of two parts which are coupled with an air gap distance. A functionalized BioNEMS beam supports one part of the proposed metamaterial cells. When patient samples including target analytes is exposed to the NEMS beam surface, the specific bio-interactions are happened and the energy (surface stress type) is r...
Source: IEE Transactions on NanoBioscience - May 10, 2023 Category: Nanotechnology Source Type: research
Individualized Seizure Cluster Prediction Using Machine Learning and Chronic Ambulatory Intracranial EEG
Epilepsy patients often experience acute repetitive seizures, known as seizure clusters, which can progress to prolonged seizures or status epilepticus if left untreated. Predicting the onset of seizure clusters is crucial to enable patients to receive preventative treatments. Additionally, studying the patterns of seizure clusters can help predict the seizure type (isolated or cluster) after observing a just occurred seizure. This paper presents machine learning models that use bivariate intracranial EEG (iEEG) features to predict seizure clustering. Specifically, we utilized relative entropy (REN) as a bivariate feature ...
Source: IEE Transactions on NanoBioscience - May 10, 2023 Category: Nanotechnology Source Type: research
Prediction of Cancer Metastasis Using Correlations Between miRNAs and Competing Endogenous RNAs
Cancer metastasis is a complex process which involves the spread of tumor cells from the primary site to other parts of the body. Metastasis is the major cause of cancer mortality, accounting for about 90% of cancer deaths. Metastasis is primarily diagnosed by clinical examinations and imaging techniques, but such a diagnosis is made after metastasis has occurred. Prediction or early detection of metastasis is important for treatment planning since it has an impact on the survival of patients. Recently a few methods have been developed to predict lymph node metastasis, but few methods are available for predicting distant m...
Source: IEE Transactions on NanoBioscience - May 10, 2023 Category: Nanotechnology Source Type: research
Implementation of an Ultrasensitive Biomolecular Controller for Enzymatic Reaction Processes With Delay Using DNA Strand Displacement
In this article, a set of abstract chemical reactions has been employed to construct a novel nonlinear biomolecular controller, i.e, the Brink controller (BC) with direct positive autoregulation (DPAR) (namely BC-DPAR controller). In comparison to dual rail representation-based controllers such as the quasi sliding mode (QSM) controller, the BC-DPAR controller directly reduces the number of CRNs required for realizing an ultrasensitive input-output response because it does not involve the subtraction module, reducing the complexity of DNA implementations. Then, the action mechanism and steady-state condition constraints of...
Source: IEE Transactions on NanoBioscience - May 9, 2023 Category: Nanotechnology Source Type: research
ViTScore: A Novel Three-Dimensional Vision Transformer Method for Accurate Prediction of Protein–Ligand Docking Poses
We present a novel deep learning-based scoring function for ranking protein-ligand docking poses based on Vision Transformer (ViT), named ViTScore. To recognize near-native poses from a set of poses, ViTScore voxelizes the protein-ligand interactional pocket into a 3D grid labeled by the occupancy contribution of atoms in different physicochemical classes. This allows ViTScore to capture the subtle differences between spatially and energetically favorable near-native poses and unfavorable non-native poses without needing extra information. After that, ViTScore will output the prediction of the root mean square deviation (r...
Source: IEE Transactions on NanoBioscience - May 9, 2023 Category: Nanotechnology Source Type: research
Antibacterial and Anti-Biofilm Activities of Microbial Synthesized Silver and Magnetic Iron Oxide Nanoparticles Against Pseudomonas aeruginosa
In this study, we focused our attention on the antibacterial and anti-biofilm activities of various microbial synthesized silver (nano-Ag) and magnetic iron oxide (nano-Fe3O4) nanoparticles against clinical isolates of P. aeruginosa that displayed ceftazidime resistance. The nano-Ag and nano-Fe3O4 represented great antibacterial properties. Nano-Ag and nano-Fe3O4 exhibited a reduction in the biofilm formation by P. aeruginosa reference strain as determined by crystal violet and XTT assays and light microscopy method. Among all, nano-Ag-2 and 7 owing to inherent attributes and mechanisms of resistance in the bacterial biofi...
Source: IEE Transactions on NanoBioscience - April 18, 2023 Category: Nanotechnology Source Type: research
Inhibitory Impacts of Fulvic Acid-Coated Iron Oxide Nanoparticles on the Amyloid Fibril Aggregations
Alzheimer’s disease is considered as multi-factor diseases, the main hallmarks of which are extracellular amyloid-beta and intracellular tau protein aggregations, leading to neural death. With this in mind, most of the studies have been focused on eliminating these aggregations. Fulvic acid is one of the polyphenolic compounds which exhibits strong anti-inflammation and anti-amyloidogenic effects. On the other hand, iron oxide nanoparticles are able to reduce/eliminate the amyloid aggregations. Here in, the effect of fulvic acid-coated iron-oxide nanoparticles on the commonly used in-vitro model for amyloid aggregation s...
Source: IEE Transactions on NanoBioscience - April 14, 2023 Category: Nanotechnology Source Type: research
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Source: IEE Transactions on NanoBioscience - April 1, 2023 Category: Nanotechnology Source Type: research
Construction of Bimetallic Hybrid Multishell Hollow Spheres via Sequential Template Approach for Less Cytotoxic Antimicrobial Effect
This work has aimed to synthesize less cytotoxic but antibacterial effective materials. Here we synthesized zinc, titanium nanoparticles based multishell hollow spheres (ZnO@TiO2 MSHS) via sequential template approach (STA) and studied their comparative antimicrobial activity with pure zinc and titanium nanoparticles (NPs). Various techniques have been used to explore the physico-chemical properties of the hybrid shells (ZnO@TiO2 MSHS). FTIR, XRD measurements approved the enhanced crystallinity of synthesized hybrid MSHS via STA technique constructed by ZnO, TiO2 NPs. The optical transmittance was enhanced 67...
Source: IEE Transactions on NanoBioscience - April 1, 2023 Category: Nanotechnology Source Type: research
Temperature Imposed Sensitivity Issues of Hetero-TFET Based pH Sensor
An underlapped hetero-structure electrolyte Bio-TFET for potential of hydrogen (pH) sensing has been presented in this article. Intersection charge density ( ${text{D}_{text{it}}}$ ) near the substrate-oxide junction can be employed to represent pH value within the simulation. A feasible fabrication scheme for the proposed model is specified here. A detailed simulation is performed with an ATLAS device simulator to examine the efficiency of the projected sensor. The impact of pH alterations on device features akin to the drain current ( ${text{I}_{text{DS}}}$ ), threshold potential ( ${text{V}_{text{TH}}}$ ), sensitivity r...
Source: IEE Transactions on NanoBioscience - April 1, 2023 Category: Nanotechnology Source Type: research
