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Related Concept Videos

Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
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Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Fast Fourier Transform01:10

Fast Fourier Transform

The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
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Multimachine Stability01:25

Multimachine Stability

Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
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Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
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Related Experiment Video

Updated: May 22, 2026

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)
07:19

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Published on: June 28, 2017

Tempest: GPU-CPU computing for high-throughput database spectral matching.

Jeffrey A Milloy1, Brendan K Faherty, Scott A Gerber

  • 1Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire 03756, USA.

Journal of Proteome Research
|May 30, 2012
PubMed
Summary
This summary is machine-generated.

Tempest, a new GPU-accelerated software, significantly speeds up peptide identification from mass spectrometry data. This high-throughput proteomics tool offers cluster-level performance on a desktop computer.

Related Experiment Videos

Last Updated: May 22, 2026

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)
07:19

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Published on: June 28, 2017

Area of Science:

  • Proteomics
  • Computational Biology
  • Bioinformatics

Background:

  • Mass spectrometry generates vast amounts of data, creating a bottleneck in peptide identification.
  • Shotgun sequencing and complex experimental designs (PTMs, isotopic labeling) further strain computational resources.

Purpose of the Study:

  • To develop a high-throughput database searching program for peptide spectral matching.
  • To leverage graphical processing unit (GPU) capabilities for accelerated proteomics data analysis.

Main Methods:

  • Developed Tempest, a program combining CPU-based database digestion/indexing and GPU-based similarity scoring.
  • Implemented full theoretical peptide fragmentation spectra generation and comparison on the GPU.
  • Introduced an 'Accelerated Score' for high-resolution MS/MS spectra, complementing the SEQUEST XCorr score.

Main Results:

  • Tempest achieves very high throughput for peptide spectral matching.
  • The GPU implementation enables efficient similarity scoring, including theoretical spectrum generation.
  • The new 'Accelerated Score' provides accuracy comparable to XCorr for high-resolution data.

Conclusions:

  • Tempest offers a cost-effective solution for high-performance proteomics data analysis.
  • The software significantly reduces the computational bottleneck in identifying peptides from mass spectrometry data.
  • GPU acceleration provides cluster-level performance on an affordable desktop computer.