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VIBRANT: spectral profiling for single-cell drug responses
High-content cell profiling has proven invaluable for single-cell phenoty** in response to chemical perturbations. However, methods with improved...
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Development of Spectral Imaging Cytometry
Spectral flow cytometry is a new technology that enables measurements of fluorescent spectra and light scattering properties in diverse cellular...
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Spectral Flow Cytometry Analysis of Resident Tissue Macrophages
Spectral flow cytometry improves flow cytometry panels by resolving the full emission spectra of individual fluorophores, allowing greater...
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A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology
Since genes do not function individually, the gene module is considered an important tool for interpreting gene expression profiles. In order to...
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Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture
Neuronal oscillations are commonly analyzed with power spectral methods that quantify signal amplitude, but not rhythmicity or ‘oscillatoriness’ per...
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SGCP: a spectral self-learning method for clustering genes in co-expression networks
BackgroundA widely used approach for extracting information from gene expression data employs the construction of a gene co-expression network and...
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scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching
Single-cell RNA sequencing has been instrumental in uncovering cellular spatiotemporal context. This task is challenging as cells simultaneously...
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splitSMLM, a spectral demixing method for high-precision multi-color localization microscopy applied to nuclear pore complexes
Single molecule localization microscopy (SMLM) with a dichroic image splitter can provide invaluable multi-color information regarding colocalization...
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Live-cell fluorescence spectral imaging as a data science challenge
Live-cell fluorescence spectral imaging is an evolving modality of microscopy that uses specific properties of fluorophores, such as excitation or...
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Identification of important gene signatures in schizophrenia through feature fusion and genetic algorithm
Schizophrenia is a debilitating psychiatric disorder that can significantly affect a patient’s quality of life and lead to permanent brain damage....
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clusterMaker2: a major update to clusterMaker, a multi-algorithm clustering app for Cytoscape
BackgroundSince the initial publication of clusterMaker , the need for tools to analyze large biological datasets has only increased. New datasets...
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Mass spectrometry DDA parameters and global coverage of the metabolome: Spectral molecular networks of momordica cardiospermoides plants
IntroductionMolecular networking (MN) has emerged as a key strategy to organize and annotate untargeted tandem mass spectrometry (MS/MS) data...
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Supervised learning algorithm for analysis of communication signals in the weakly electric fish Apteronotus leptorhynchus
Signal analysis plays a preeminent role in neuroethological research. Traditionally, signal identification has been based on pre-defined signal...
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Detecting the attack of the fall armyworm (Spodoptera frugiperda) in cotton plants with machine learning and spectral measurements
The Spodoptera frugiperda (i.e., fall armyworm) causes irreversible damage in cotton cultivars, and its visual inspection on plants is a burdensome...
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Downscaling UAV land surface temperature using a coupled wavelet-machine learning-optimization algorithm and its impact on evapotranspiration
Monitoring evapotranspiration (ET) is possible through land surface temperature (LST) measured by satellites and unmanned aerial vehicles (UAV). The...
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Spectral characterization and classification of two different crown root rot and vascular wilt diseases (fusarium oxysporum f.sp. radicis lycopersici and fusarium solani) in tomato plants using different machine learning algorithms
Fusarium oxysporum f.sp. radicis lycopersici (FORL) and Fusarium solani (F.S.) are common fungi responsible for crown root rot and vascular wilt...
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INFLECT: an R-package for cytometry cluster evaluation using marker modality
BackgroundCurrent methods of high-dimensional unsupervised clustering of mass cytometry data lack means to monitor and evaluate clustering results....
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The Time-Frequency Spectral Analysis and Applications in Bioinformatics
In signal processing, time-frequency analysis encompasses a set of techniques that study a signal across both time and frequency domains...