Software

The files contain software, instructions, and in some cases, example applications:

SGN Sim

by Andre S. Ribeiro and Jason Lloyd-Price: https://drive.google.com/open?id=1fGY1PyEwC5cDmNSEbAbhn12Kponur4GG

January 13, 2007.

 Reference: Andre S. Ribeiro; Jason Lloyd-Price, (2007) SGN Sim, a Stochastic Genetic Networks Simulator, Bioinformatics, 23(6):777-779. doi:10.1093/bioinformatics/btm004.

1) Exs.pdf  - pdf with all described examples and results.

2) man_sgns.pdf - manual for the dynamics simulator

3) man_sgne.pdf - manual for the networks ensemble generator

4) Examples_Reactions.zip - Files of reactions and ensemble parameters for all examples

SGNS2 Stochastic Simulator

by Jason Lloyd-Price, Abhishekh Gupta, Andre S. Ribeiro

Introduction

SGNS2 is an open source stochastic chemical kinetics simulator written in C++. It uses and expands upon the Next Reaction Method to include dynamic compartments, multi-delayed reactions, and several stochastic molecules partitioning schemes which can be applied on a per-molecule-type basis during cell division.

If you use SGNS2 , please cite: J. Lloyd-Price, A. Gupta, and A. S. Ribeiro (2012) SGNS2: A Compartmentalized Stochastic Chemical Kinetics Simulator for Dynamic Cell Populations. Bioinformatics, 28(22):3004-5, doi: 10.1093/bioinformatics/bts556.

Download

The current version is 2.1.170, updated 24.1.2017. Documentation is included.

Download: SGNS2

Example models are available SGNS2, and include:

CellLine, a stochastic cell lineage simulator.

by Andre S. Ribeiro, Daniel A. Charlebois and Jason Lloyd-Price. July 23, 2007.

 Reference: A.S. Ribeiro, D. Charlebois, J. Lloyd-Price (2007) CellLine, a stochastic cell lineage simulator, Bioinformatics 23(24):3409-3411. DOI: 10.1093/bioinformatics/btm491

 The simulator is available here: CellLine

1) Examples.pdf  - pdf with examples and results.

2) manual_CellLine.pdf - manual for CellLine usage

3) Examples_Reactions.zip - Files of reactions for all examples

 

Mytoe, automatic analysis of mitochondrial dynamics.

by E. Lihavainen, J. Mäkelä, J. N. Spelbrink, and A. S. Ribeiro (2012). 17.1.2012: Version 1.0.

Mytoe is a software for analyzing mitochondrial dynamics from fluorescence microscope images. The program can be used for the analysis of spatial properties of the mitochondrial structure, as well as the motion of mitochondria. Mytoe is implemented in MATLAB. In addition to the source code, a standalone Windows version is available, which does not require a MATLAB installation.

Reference: E. Lihavainen, J. Mäkelä, J. N. Spelbrink, and A. S. Ribeiro (2012) Mytoe: Automatic analysis of mitochondrial dynamics. Bioinformatics 7(28): 1050-1051. 

Download: Mytoe

The file contains: MATLAB source code, and Windows standalone version. We also provide a set of confocal microscope images of a U2OS human osteosarcoma cell with fluorescently labeled mitochondria, nucleus and cell membrane. Finally, there are example images and data, user's manual, and a supplementary file.

Last update: 18.07.2016

CellAging

Introduction

CellAging is a tool designed to automatically extract information on the segregation of aggregates to the cell poles and their partitioning in division and on cellular vitality from temporal images of E. coli cells, obtained by parallel brightfield and fluorescence microscopy. CellAging performs cell segmentation from brightfield images, alignment of brightfield and fluorescence images, lineage construction and pole age determination, and computation of aging-related features. An example of its use analyzing tsr-venus protein distributions from live cell images across a few generations can also be downloaded below.

Reference: A. Häkkinen, A.-B. Muthukrishnan, A. Mora, J.M. Fonseca, and A.S. Ribeiro (2013) CellAging: A tool to study segregation and partitioning in division in cell lineages of Escherichia coli. Bioinformatics 29 (13): 1708-1709. doi: 10.1093/bioinformatics/btt194

Downloads: CellAging 

MAMLE: Cell segmentation by multi-resolution analysis and maximum likelihood estimation

by S Chowdhury, M Kandhavelu, O Yli-Harja, and Andre S Ribeiro

MAMLE is a segmentation method for detecting cells within dense clusters. MAMLE executes cell segmentation in two main stages. The first relies on state of the art filtering technique, edge detection in multi resolution with morphological operator and threshold decomposition for adaptive thresholding. From this, a correction procedure is applied that exploits maximum likelihood estimate as an objective function. Also, it acquires morphological features from the initial segmentation for constructing the likelihood parameter, after which the final segmentation results are obtained.

Reference: S Chowdhury, M Kandhavelu, O Yli-Harja, and AS Ribeiro (2013) Cell Segmentation by Multi-resolution Analysis and Maximum Likelihood Estimation (MAMLE). BMC Bioinformatics 14 (Sup. 10), S8.

Download: Cell Segmentation Tool

ZebIAT: Zebrafish Image Analysis Tool

About

ZebIAT is a tool for registering zebrafish images acquired by fluorescence microscope as well as differential interference microscope. The tool offers automatic and semi-automatic methods to analyze images and thus allow, e.g. quantitative comparisons between images. The tool uses a thin plate splines registration method.

Reference: T. Annila, E. Lihavainen, I.J. Marques, D.R. Williams, O. Yli-Harja and A.S. Ribeiro. 2013. ZebIAT, an image analysis tool for registering zebrafish embryos and quantifying cancer metastasis. BMC Bioinformatics 14 (Sup. 10), S5, in press.

Download: ZebIAT

MATLAB source code: Zebratool requires also some addition files in order to work. For spot detection we used wavelet segmentation algorithm based on article "Ruusuvuori et al.: Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images". For interpolation we used "inpaint" technique which can be downloaded from Mathworks:

"Inpaint"-method

"Atrouswave"-method for spot detection

We also provide a set of fluorescence microscope images of zebrafish for testing. The guide for using the tool is also provided.

Example images

User´s manual

Estimation of RNA numbers of Spots Intensities 

Reference: A Häkkinen, M Kandhavelu, S Garasto, and AS Ribeiro (2014) Estimation of fluorescence-tagged RNA numbers from spot intensities. Bioinformatics 30(8), 1146-1153.  DOI: 10.1093/bioinformatics/btt766

 The software tools are available for Windows here: RNANumbers 

For information, start by reading the file "readme.txt"

Rate Limiting Steps in Transcription from RNA production times in live cells 

by Antti Häkkinen and Andre S Ribeiro, 2016.

Reference: A Häkkinen and AS Ribeiro (2016) Characterizing Rate Limiting Steps in Transcription from RNA Production Times in Live Cells. Bioinformatics. 32(9): 1346-1352. DOI: 10.1093/bioinformatics/btv744

The software tools are available for Windows XP here: RateLimit

For information, start by reading the file "readme.txt"

SCIP: A Single-Cell Image Processor Toolbox

by Leonardo Martins, Ramakanth Neeli-Venkata, Samuel M.D. Oliveira, Jose M. Fonseca, and Andre S. Ribeiro (https://academic.oup.com/bioinformatics/article/34/24/4318/5042173 )

Introduction

SCIP, written in MatLab, is an open source multi-channel, multi-process, time-lapse morphological and functional microscopy images analyser. 

If you use SCIP, please cite: L Martins, R Neeli-Venkata, SMD Oliveira, A Häkkinen, AS Ribeiro, and JM Fonseca (2018) SCIP: A Single-Cell Image Processor toolbox. Bioinformatics 34(24), 4318–4320. DOI: 10.1093/bioinformatics/bty505 . 

Download: http://www.ca3-uninova.org/project_scip