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Results for “Signal-To-Noise Ratio”

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At least 19 recordsLinked to original sources
PubMed2025

A neural network model enables worm tracking in challenging conditions and increases signal-to-noise ratio in phenotypic screens.

High-resolution posture tracking of C. elegans has applications in genetics, neuroscience, and drug screening. While classic methods can reliably track isolated worms on uniform backgrounds, they fail when worms overlap, coil, or move in complex environments. Model-based tracking and deep learning approaches have addressed these issues to an extent, but there is still significant room for improvement in tracking crawling worms. Here we train a version of the DeepTangle algorithm developed for swimming worms using a combination of data derived from Tierpsy tracker and hand-annotated data for more difficult cases. DeepTangleCrawl (DTC) outperforms existing methods, reducing failure rates and producing more continuous, gap-free worm trajectories that are less likely to be interrupted by collisions between worms or self-intersecting postures (coils). We show that DTC enables the analysis of previously inaccessible behaviours and increases the signal-to-noise ratio in phenotypic screens, even for data that was specifically collected to be compatible with legacy trackers including low worm density and thin bacterial lawns. DTC broadens the applicability of high-throughput worm imaging to more complex behaviours that involve worm-worm interactions and more naturalistic environments including thicker bacterial lawns.

Caenorhabditis elegans↗
PubMed2024

Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data.

The uncovering of protein-RNA interactions enables a deeper understanding of RNA processing. Recent multiplexed crosslinking and immunoprecipitation (CLIP) technologies such as antibody-barcoded eCLIP (ABC) dramatically increase the throughput of mapping RNA binding protein (RBP) binding sites. However, multiplex CLIP datasets are multivariate, and each RBP suffers non-uniform signal-to-noise ratio. To address this, we developed Mudskipper, a versatile computational suite comprising two components: a Dirichlet multinomial mixture model to account for the multivariate nature of ABC datasets and a softmasking approach that identifies and removes non-specific protein-RNA interactions in RBPs with low signal-to-noise ratio. Mudskipper demonstrates superior precision and recall over existing tools on multiplex datasets and supports analysis of repetitive elements and small non-coding RNAs. Our findings unravel splicing outcomes and variant-associated disruptions, enabling higher-throughput investigations into diseases and regulation mediated by RBPs.

RNA-Binding Proteins↗
PubMed2025

Genome-wide profiling the integration patterns with T7-PCR.

Integration of exogenous gene fragments into the host genomes is a widely used and powerful method for studying gene functions, advancing molecular breeding, and conducting gene therapy. Accurately identifying the integration sites is essential for ensuring both the safety and efficacy of genome engineering efforts. However, current mapping techniques are constrained by high costs and a low signal-to-noise ratio. In this study, we developed an innovative tool for mapping integration sites, leveraging T7 polymerase-mediated in vitro transcription (T7-IVT) to capture the junction fragments surrounding integration loci. This approach converts genomic flanking sequences into RNA, enabling the simultaneous enrichment of junction fragments and the elimination of background genomic DNA, thereby significantly enhancing the signal-to-noise ratio. We have validated the efficiency of this method, named T7-PCR, across yeast, plant, and human cells under diverse integration scenarios. T7-PCR outperforms current next-generation sequencing (NGS)-based mapping strategies in terms of efficiency and accuracy, with minimal positional effects. This method is highly applicable for high-throughput transgene screening and also supports the development of next-generation tools for targeted integration of large fragments.

Humans↗
PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗
PubMed2026

Shielding performance and clinical applicability of lead-free materials in computed tomography.

Owing to the high radiation exposure associated with computed tomography (CT) examinations and the image quality degradation caused by conventional radiation shielding materials, this study evaluated the dose reduction performance and image quality maintenance potential of a newly developed lead-free composite shielding material. This material was composed of bismuth, tungsten, tungsten carbide, aluminium, and polyurethane. Phantom-based dose measurements demonstrated that the shielding material achieved dose reduction rates ranging from 17.6% to 37.6%, depending on tube voltage. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and changes in tube current-time product (mAs) under a scout-based automatic exposure control (AEC) protocol were analysed according to the presence or absence of the shielding material across regions. For the clinical evaluation, CT scans were performed on four patients. Furthermore, the images were reviewed to evaluate whether this material affected image quality. The shielding material exhibited radiation reduction levels comparable to those reported in previous studies. SNR and CNR analyses showed minor statistical variations in certain regions; however, most differences were not statistically significant, and even significant differences remained within a range that did not compromise diagnostic image quality. Under the scout-based AEC protocol, the use of the shielding material resulted in less than 1% variation in mAs values. No visually perceptible artefacts or clinically significant image quality degradation were observed. The proposed composite shielding material demonstrated the potential to mitigate some limitations of conventional shielding materials and showed preliminary clinical feasibility as an adjunctive strategy for radiation dose reduction in CT examinations.

Radiation Protection↗
PubMed1975

An on-line transformation of EEG scalp potentials into orthogonal source derivations.

A new type of EEG derivation has been investigated. This derivation, constituting a practical implementation of the Laplace operator, detects source activity as it appears at the surface level of the scalp. It is realized in the 10-20 system of electrode placement basically as an analogue superposition of four bipolar derivations, forming a star-like configuration around each electrode. Visual estimation of the topographical origins of a pattern, is thus replaced by a more efficient on-line process, which derives the source activity at the position of each individual electrode. Practical correlation tests have shown that the separation of adjacent derivations is improved by a factor of between two and four, compared to the corresponding bipolar and common reference derivations. Any feature of local origin will therefore have a correspondingly increased signal-to-noise ratio prior to the stage of visual or automatic interpretation. As a consequence of the partition of the scalp field into 19 source zreas, instead of utilizing an arbitrary number of potential differences, one fixed montage with 19 recorder channels is sufficient to present the total surface activity, within the limits of resolution of the electrode system.

Data Display↗
PubMed1975

Detection of neuroelectric signals from multiple data channels by optimum linear filter methods.

A general mathematical formulation for predicting achievable levels of detection of neuroelectric signals in associated background noise is provided for the case where such data are obtainable from multiple recording loci. The formulation depends upon the signal-to-noise ratios and bandwidths of the incorporated data channels and on the degree of noise dependency between channels. The signals are assumed to relate to the same event such as the production of an incipient movement but need not have the same waveshape. The detection technique is based upon passage of the data through a series of optimum linear filters. The outputs of the filters can either be summated in analog fashion prior to making the detection decision, or their separate outputs and separate detection decisions can be treated combinatorially to determine a detection decision for the aggregate. The former method is superior to the latter for small numbers of data channels. The latter method may be preferable where variation in signal latency exists between channels. Incorporation of information from multiple channels with independent noise can result in significant improvement over detection signals from a single channel provided that the signal-to-noise level of each additional channel exceeds that of the aggregate divided by square rootK, K being the total number of added channels. However, the presence of noise dependency between channels may severly restrict the degree of imporvement realizable through the multiple channel detection operation, irrespective of the number of added cha-nels. The implication of this result on the possibility of using EEG signals predicting incipient movement to control the operation of a motor prosthesis is profound. Inter-channel noise dependency with correlation coefficienr filter method of detection levels required for prosthesis operation. Zero lag correlation coefficients between electrical recordings from separate cortical loci both in man a

Animals↗
PubMed1978

Activity of human hippocampal formation and amygdala neurons during memory testing.

Single and multiple unit recordings were made from fine wires stereotaxically implanted in the hippocampus (HC), hippocampal gyrus (HCG), and amygdala (Am) of psychomotor epileptics. During a series of memory and control tests presented on slides, 21 of 155 HCG units, 15 of 59 HC units, and 2 of 54 Am units showed what appeared to be simple phasic or tonic visual responses. Twenty-seven other units, found only in the HCG, changed firing only during slides requiring a choice ('choice units'). A given choice unit responded during choices indicated verbally or manually, and during tasks requiring recall of Recent Memory, various visual discriminations, and expressions of preference. Choice units were not affected by sensory stimulation or motor activity in contexts not requiring choice. Phasically inhibited choice units had higher firing rates and lower signal-to-noise ratios than tonically excited units. Whether an electrode recorded a choice unit was unrelated to if it recorded a response to hyperventilation, or was in an area of epileptic pathology. Recordings were also made during an interview lasting several hours and eliciting a wide range of behaviors. Five of the 131 HCG units fired in repeated extended bursts, at least 50 times background during recall of word pairs or of the patient's hospital room. The unit response did not occur during numerous control tasks possessing similar overt sensory, motor, and social concomitants, but not requiring Recent Memory.

Action Potentials↗
PubMed1978

Signal to noise ratio and response variability measurements in single trial evoked potentials.

Techniques were developed for measurement of signal to noise ratio and response variability in single trial evoked potentials. These techniques were extended and verified using a digital computer simulation of signal plus noise trials. When applied to real data the measures appear to have high reliability and to demonstrate that human evoked potentials are more variable than would be expected from background noise variation alone. Empirical equations are presented which can be applied to existing single trial EP data to estimate both signal-to-noise ratio and its expected variance.

Adult↗
PubMed1979

Evaluation of the Wiener filter applied to evoked EMG potentials.

The application of the Wiener filter to the estimation of responses evoked in the tonic EMG activity of tibialis anterior by cutaneous electrical stimulation of the foot is described. The effectiveness of the filter is assessed using both experimental and simulated data by computing the mean square error between the actual evoked potential and ensemble average and Wiener filter estimates of it. The Wiener filter is shown to provide a better estimate of the final response than simple ensemble averaging. The improvement is most marked in cases where the signal-to-noise ratio is small, but the Wiener filter estimate is always better than the ensemble average estimate. It is concluded that Wiener filtering significantly reduces the number of responses required to obtain a good estimate of the evoked potential in this experimental situation.

Computers↗
PubMed2026

Advances in Single-Molecule Immunoassay: From Counting Strategies to CRISPR-Enhanced Biosensing.

Single-molecule immunoassays (SMIs) overcome the sensitivity limitations of conventional bulk measurements by enabling a paradigm shift from analog to digital signal readouts, thereby facilitating highly sensitive quantification of ultra-low-abundance biomarkers for precision diagnostics. This review provides a systematic overview of recent advances in SMI technologies and the conceptual framework underlying their evolution. First, discretization strategies for single-molecule counting are classified into hard discretization, based on physical confinement, and soft discretization, based on spatiotemporal isolation, within heterogeneous and homogeneous assay systems, respectively. The fundamental mechanisms by which these strategies mitigate diffusion limitations and enhance signal-to-noise ratios are discussed. Second, the integration of SMIs with CRISPR-based diagnostic systems (CRISPR-dx) is examined, with particular emphasis on their complementary roles in target recognition and signal amplification. Finally, recent applications of SMIs in the diagnosis of oncological, neurological, infectious, and cardiovascular diseases are summarized, along with a critical discussion of current engineering challenges and future directions toward clinical translation.

Immunoassay↗
PubMed2025

The offonome reveals on and off states of gene expression near the detection limit of RNA-seq.

RNA-seq, widely used for gene expression profiling, provides nucleotide level genome coverage and summary gene expression values. Generally, low-expressed genes are ignored due to their unfavorable signal-to-noise ratio, however, these genes may offer crucial information, such as detecting rare cells in bulk tissues. In this study, we applied an approach that transforms the expression levels of low-expressed genes into a robust dichotomized on/off state by leveraging similarities in transcript coverage shape. Applied to three human cancer cohorts from the Cancer Genome Atlas (TCGA), chosen based on tissue morphology and anatomic site, we identified genes, the "offonome" near the detection limit, consistently or occasionally off across samples. Genes in the offonome spectrum proved useful for supervised and unsupervised applications, including characterizing oncogenic pathways, and identifying rare populations of cells in bulk tissue. Interrogating the offonome is relevant to bulk tumor analyses like TCGA, potentially expediting gene investigation in low-input situations like single cell RNA-seq.

Humans↗
PubMed2025

Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes.

Chromosome Conformation Capture (3 C) methods, including Hi-C (a high-throughput variation of 3 C), detect pairwise interactions between DNA regions, enabling the reconstruction of chromatin architecture in the nucleus. HiChIP is a modification of the Hi-C experiment that includes a chromatin immunoprecipitation (ChIP) step, allowing genome-wide identification of chromatin contacts mediated by a protein of interest. In mammalian cells, cohesin protein complex is one of the major players in the establishment of chromatin loops. We present an improved cohesin HiChIP experimental protocol. Using comprehensive bioinformatic analysis, we show that a dual chromatin fixation method compared to the standard formaldehyde-only method, results in a substantially better signal-to-noise ratio, increased ChIP efficiency and improved detection of chromatin loops and architectural stripes. Additionally, we propose an automated pipeline called nf-HiChIP ( https://github.com/SFGLab/hichip-nf-pipeline ) for processing HiChIP samples starting from raw sequencing reads data and ending with a set of significant chromatin interactions (loops), which allows efficient and timely analysis of multiple samples in parallel, without requiring additional ChIP-seq experiments. Finally, using advanced approaches for biophysical modelling and stripe calling we generate accurate loop extrusion polymer models for a region of interest and provide a detailed picture of architectural stripes, respectively.

Chromatin↗
PubMed2026

A smartphone-integrated plasmonic biosensor for amplification-free detection of African swine fever virus.

African Swine Fever Virus (ASFV) poses a catastrophic threat to global swine production, with recent outbreaks across Europe, Asia, and the Caribbean, significantly elevating the biosecurity risk to the United States' billion-dollar pork industry. Current diagnostic gold standards are laboratory-dependent and introduce critical delays in outbreak response. To address this gap, a plasmonic biosensor based on functionalized gold nanoparticles (GNPs) was developed for the rapid, amplification-free detection of ASFV. GNPs were surface-functionalized with 11-mercaptoundecanoic acid (MUDA) and combined in situ with ASFV-specific oligonucleotide probes targeting a conserved region of the p72 (B646L) gene. The detection mechanism relies on acid-induced aggregation: hybridization of target ASFV DNA to the probe generates a rigid duplex that shields the nanoparticles from acid-induced destabilization, maintaining a ruby-red color, whereas in the absence of target DNA the GNPs aggregate, producing a visible red-to-blue color shift. The optimized plasmonic biosensor demonstrated 100% analytical specificity, with no cross-reactivity against a panel of 19 non-target bacterial genomic DNA samples representative of the swine environment. Detection limits determined by the IUPAC 3σ criterion were 285 copies per reaction for Probe 1 and 402 copies per reaction for Probe 2, within the same order of magnitude as the qPCR reference assay run on the same dilution series (approximately 312 copies per reaction) under the experimental conditions used here. A smartphone-based Bio-Analytics App employing an RGB color-conversion algorithm served as a quantitative reader, yielding signal-to-noise ratios (S/N) that strongly correlated with benchtop spectrophotometric readings (A520/A620 ratio, R2 = 0.96) and achieved diagnostic concordance with qPCR binary calls. This platform offers a robust and low-cost (∼$2 per test), amplification-free approach to ASFV screening with potential for point-of-need deployment, subject to future validation in clinical specimens.

Journal Article↗
PubMed2025

Unicorn: enhancing single-cell Hi-C data with blind super-resolution for 3D genome structure reconstruction.

MOTIVATION: Single-cell Hi-C (scHi-C) data provide critical insights into chromatin interactions at individual cell levels, uncovering unique genomic 3D structures. However, scHi-C datasets are characterized by sparsity and noise, complicating efforts to accurately reconstruct high-resolution chromosomal structures. In this study, we present ScUnicorn, a novel blind super-resolution framework for scHi-C data enhancement. ScUnicorn uses an iterative degradation kernel optimization process, unlike traditional super-resolution approaches, which rely on downsampling, predefined degradation ratios, or constant assumptions about the input data to reconstruct high-resolution interaction matrices. Hence, our approach more reliably preserves critical biological patterns and minimizes noise. Additionally, we propose 3DUnicorn, a maximum likelihood algorithm that leverages the enhanced scHi-C data to infer precise 3D chromosomal structures. RESULTS: Our evaluation demonstrates that ScUnicorn achieves superior performance over the state-of-the-art methods in terms of Peak Signal-to-Noise Ratio, Structural Similarity Index Measure, and GenomeDisco scores. Moreover, 3DUnicorn's reconstructed structures align closely with experimental 3D-FISH data, underscoring its biological relevance. Together, ScUnicorn and 3DUnicorn provide a robust framework for advancing genomic research by enhancing scHi-C data fidelity and enabling accurate 3D genome structure reconstruction. AVAILABILITY AND IMPLEMENTATION: Unicorn implementation is publicly accessible at https://github.com/OluwadareLab/Unicorn.

Single-Cell Analysis↗
PubMed2025

Automated chromatin profiling with spa-ChIP-seq uncovers the impacts of condition variations.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to study the genomic localization of DNA-associated proteins. However, conventional protocols include multiple manual steps that can introduce inconsistency and limit scalability, thereby restricting the inclusion of appropriate replicates and controls. Although the introduction of liquid handling platforms has improved reproducibility, most existing efforts have automated only a subset of the workflow, and extending automation to efficiently map non-histone proteins, such as chromatin regulators, remains challenging. Here, we present a fully automated implementation of our previously developed single-pot ChIP-seq protocol (Texari et al. 2021), named spa-ChIP-seq, which enables scalable processing of 8 to 96 ChIP-seq samples from crosslinked cells to sequencing-ready library in approximately three days with an estimated cost of $70 per sample. Benchmarking spa-ChIP-seq against manual ChIP-seq performed in parallel demonstrates comparable signal-to-noise ratio between the two workflows. Using spa-ChIP-seq, we systematically evaluate multiple parameters including shearing and crosslinking conditions, buffer compositions, and the ratio of antibody to cell-number. We find, for the first time to our knowledge, that weaker genomic localization signals are sensitive to changing the antibody to cell-number ratio, whereas the stronger signals remain unaffected. This finding underscores the importance of maintaining consistent antibody-to-cell-number ratio for comparative studies, such as treatment responses or chromatin-QTL mapping. The spa-ChIP-seq protocol is publicly available, including deck setups, operational parameters, and scripts. We envision that this robust, cost-efficient protocol will facilitate high-throughput, reproducible ChIP-seq analyses, supporting large-scale studies of antibody validation, compound screening, population genomics, and diagnostic frameworks.

Journal Article↗