Spectral Analysis Programs
Spectral Analysis Programs - Related Videos
11:08
Analysis of Cell Suspensions Isolated from Solid Tissues by Spectral Flow Cytometry
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Cited by 4 •
2017
This article describes spectral cytometry, a new approach in flow cytometry that uses the shapes of emission spectra to distinguish fluorochromes. An algorithm replaces compensations and can treat auto-fluorescence as an independent parameter. This new approach allows for the proper analysis of cells isolated from solid organs.
07:11
ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
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Cited by 1 •
2021
This protocol introduces Franck-Condon Lineshape Analyses (FCLSA) of emission spectra and serves as a tutorial for the use of ARL Spectral Fitting software. The open-source software provides an easy and intuitive way to perform advanced analysis of emission spectra including excited state energy calculations, CIE color coordinate determination, and FCLSA.
07:29
Programmed Electrical Stimulation in Mice
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Cited by 48 •
2010
Programmed electrical stimulation provides the ability to determine conduction properties of the heart, and the possibility to induce and terminate cardiac arrhythmias using various pacing protocols. Using a transvenous catheter, intracardiac electrogram recordings can be obtained in mice following programmed electrical stimulation protocols to identify arrhythmogenic substrates.
11:21
Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography
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Cited by 24 •
2013
Photoacoustic ophthalmology (PAOM), an optical-absorption-based imaging modality, provides the complementary evaluation of the retina to the currently available ophthalmic imaging technologies. We report the using of PAOM integrated with spectral-domain optical coherence tomography (SD-OCT) for simultaneous multimodal retinal imaging in rats.
14:26
In vivo Quantification of G Protein Coupled Receptor Interactions using Spectrally Resolved Two-photon Microscopy
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Cited by 6 •
2011
By employing a spectrally resolved two-photon microscopy imaging system, pixel-level maps of Förster Resonance Energy Transfer (FRET) efficiencies are obtained for cells expressing membrane receptors hypothesized to form homo-oligomeric complexes. From the FRET efficiency maps, we are able to estimate stoichiometric information about the oligomer complex under study.
FAQs
Baseline correction establishes a consistent reference for measured intensity, while smoothing reduces distracting variation before later interpretation. Peak detection then highlights prominent wavelength features. Used together, these processing steps can make spectra easier to compare and improve reproducibility when researchers characterize biological samples or examine subtle differences between measurements.
Spectral fitting provides a structured way to represent measured spectral patterns for analysis. When combined with peak detection and quantitative comparison, it helps researchers evaluate how closely spectra resemble one another or how their signals differ. This is useful when identifying or measuring biomolecules, pigments, fluorescent labels, or reaction-associated changes.
The programs can process measurements collected at different time points and compare their spectral patterns quantitatively. Shifts in the analyzed signals may indicate changes associated with an enzyme reaction, cellular process, or other biological sample behavior. Consistent correction and processing help researchers separate meaningful temporal differences from variation introduced during analysis.
A typical workflow starts by importing absorbance, fluorescence, or emission measurements from a spectrometer. Researchers then apply appropriate processing, such as baseline correction or smoothing, followed by peak detection, spectral fitting, and quantitative comparison. The resulting patterns can be interpreted in relation to biomolecules, labels, pigments, reactions, or changes in samples.
They are useful when researchers need to identify or measure biomolecules, examine pigments or fluorescent labels, monitor enzyme or cellular reactions, or evaluate sample changes over time. The programs convert instrument measurements into comparable spectral information, supporting work in biochemistry, cell biology, diagnostics, and environmental biology.
In diagnostics, processed spectral measurements can support the evaluation of biologically meaningful signal patterns and differences among samples. In environmental biology, the same analytical approach helps researchers examine spectral characteristics in biological or environmental samples. Baseline correction, fitting, and quantitative comparisons strengthen reproducibility across these investigative settings.