EM-SURFER – Navigating 3D Electron Microscopy Maps

EM-SURFER

:: DESCRIPTION

EM-SURFER is a web platform for real-time electron microscopy database search. It compares isosurface shape of a query EM map against maps in the latest EMDB.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Navigating 3D electron microscopy maps with EM-SURFER.
Esquivel-Rodríguez J, Xiong Y, Han X, Guang S, Christoffer C, Kihara D.
BMC Bioinformatics. 2015 May 30;16:181. doi: 10.1186/s12859-015-0580-6.

pyHIVE 1.0.8 – Health-related image visualization and engineering system using Python

pyHIVE 1.0.8

:: DESCRIPTION

pyHIVE was implemented as an image processing system, providing five widely used image feature engineering algorithms.

::DEVELOPER

Health Informatics Lab (HILab)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows
  • Python

:: DOWNLOAD

pyHIVE

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2018 Nov 26;19(1):452. doi: 10.1186/s12859-018-2477-7.
pyHIVE, a health-related image visualization and engineering system using Python.
Zhang R, Zhao R, Zhao X, Wu D, Zheng W, Feng X, Zhou F.

GroupTracker 1.0.1 – Video Tracking system for multiple Animals under Severe Occlusion

GroupTracker 1.0.1

:: DESCRIPTION

GroupTracker (GROUP: Gaussian Reinterpretation of OcclUsion Problem) is a multiple animal tracking system that tracks individuals under severe occlusion.

::DEVELOPER

Tsukasa Fukunaga

::REQUIREMENTS

  • Linux
  • UMATracker

:: DOWNLOAD

GroupTracker

:: MORE INFORMATION

Citation

Comput Biol Chem. 2015 Aug;57:39-45. doi: 10.1016/j.compbiolchem.2015.02.006.
GroupTracker: Video tracking system for multiple animals under severe occlusion.
Fukunaga T, Kubota S, Oda S, Iwasaki W.

Dapple 0.88pre4 – DNA Microarrays Image Analysis

Dapple 0.88pre4

:: DESCRIPTION

Dapple is a program for quantitating spots on a two-color DNA microarray image. Given a pair of images from a comparative hybridization, Dapple finds the individual spots on the image, evaluates their qualities, and quantifies their total fluorescent intensities.

Dapple is designed to work with microarrays on glass. The spot-finding techniques used are robust to uneven spot sizes and positional deviations caused by “wobbling” of the arraying robot, as well as image noise and artifacts. As long as your spots are consistently circular, Dapple has a good chance of finding them accurately.

::DEVELOPER

Jeremy Buhler

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

Dapple

:: MORE INFORMATION

Citation:

J. Buhler, T. Ideker, D. Haynor, “Dapple: Improved Techniques for Finding Spots on DNA Microarrays”, University of Washington Department of Computer Science & Engineering Technical Report UW-CSE-2000-08-05, (2000)  Supplement.

CFNet – Conic Convolution and DFT Network for classifying Microscopy Images

CFNet

:: DESCRIPTION

CFNet combines a novel rotation equivariant convolution scheme, called conic convolution, and the DFT to aid networks in learning rotation-invariant tasks. This network has been especially designed to improve performance of CNNs on automated computational tasks related to microscopy image analysis.

::DEVELOPER

Ma Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Python

:: DOWNLOAD

CFNet

:: MORE INFORMATION

Citation

Bioinformatics. 2019 Jul 15;35(14):i530-i537. doi: 10.1093/bioinformatics/btz353.
Rotation equivariant and invariant neural networks for microscopy image analysis.
Chidester B, Zhou T, Do MN, Ma J.

NEMO 1.5.2 – Analyzing Gene and Chromosome Territory Distributions from 3D-FISH Experiments

NEMO 1.5.2

:: DESCRIPTION

NEMO is a new Smart 3D-FISH (Three-dimensional fluorescence in situ hybridization) graphical user interface which provides all information in the same place so that results can be checked and validated efficiently.

::DEVELOPER

NEMO team

:: SCREENSHOTS

NEMO

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Java
  • ImageJ

:: DOWNLOAD

 NEMO

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Mar 1;26(5):696-7. doi: 10.1093/bioinformatics/btq013. Epub 2010 Jan 14.
NEMO: a tool for analyzing gene and chromosome territory distributions from 3D-FISH experiments.
Iannuccelli E1, Mompart F, Gellin J, Lahbib-Mansais Y, Yerle M, Boudier T.

Imaris 9.3.1 – Analysis, Segmentation and Interpretation of 3D and 4D Microscopy datasets

Imaris 9.3.1

:: DESCRIPTION

Imaris is a scientific software module for data visualization, analysis, segmentation and interpretation of 3D and 4D microscopy datasets.

::DEVELOPER

Imaris team

:: SCREENSHOTS

Imaris

:: REQUIREMENTS

  • Windows/MacOsX

:: DOWNLOAD

 Imaris

:: MORE INFORMATION

ACC 1.1 – Advanced Cell Classifier

ACC 1.1

:: DESCRIPTION

ACC is a data analyzer program for High Content Screening experiment to more accurately identify different phenotypes. The basic aim is to provide a very accurate analysis with minimal user interaction using advanced machine learning methods.

::DEVELOPER

RNAi Image-based Screening Centre (RISC)

:: SCREENSHOTS

ACC

::REQUIREMENTS

  • Windows/Linux/MacOsX
  • matlab

:: DOWNLOAD

 ACC

:: MORE INFORMATION

Citation

T. Wild, P. Horvath, E. Wyler, B. Widmann, L. Badertscher, I. Zemp, K. Kozak, G. Csusc, E. Lund, and U. Kutay. 2010
A protein inventory of human ribosome biogenesis reveals an essential function of Exportin 5 in 60S subunit export.
PLoS Biol 8(10): e1000522. doi:10.1371/journal.pbio.1000522

LeafNet 0.0.1 – A CNN for Plant Identification

LeafNet 0.0.1

:: DESCRIPTION

LeafNet is a method based on a convolutional neural network (CNN) to identify plants from images of leaves.

::DEVELOPER

BioInfWeb projects

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Perl

:: DOWNLOAD

LeafNet

:: MORE INFORMATION

Citation

LeafNet: A computer vision system for automatic plant species identification
Author links open overlay panelPierreBarréaBen C.StöverbKai F.MüllerbVolkerSteinhagea
Ecological Informatics Volume 40, July 2017, Pages 50-56

ImageJ 2.0.0 rc71 – Image Processing & Analysis in Java

ImageJ 2.0.0 rc71

:: DESCRIPTION

ImageJ is a public domain Java image processing program.ImageJ was designed with an open architecture that provides extensibility via Java plugins and recordable macros. Custom acquisition, analysis and processing plugins can be developed using ImageJ’s built-in editor and a Java compiler. User-written plugins make it possible to solve many image processing and analysis problems, from three-dimensional live-cell imaging, to radiological image processing, multiple imaging system data comparisons to automated hematology systems.

::DEVELOPER

ImageJ team

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

ImageJ

:: MORE INFORMATION

Citation:

Abramoff, M.D., Magelhaes, P.J., Ram, S.J. “Image Processing with ImageJ“.
Biophotonics International, volume 11, issue 7, pp. 36-42, 2004.