Downloads

Q&A page allows you to submit questions about our programs and exchange ideas with others.

 

 

Nuclei-Aware Network for Grading of Breast Cancer in HE Stained Pathological Images (Rui Yan)

Detail: http://ear.ict.ac.cn/?page_id=1985

 

A novel constrained reconstruction model towards high-resolution subtomogram averaging

Code Download: CRM-master (994 downloads)

 

PIXER: An Automated Particle-selection Method Based on Segmentation Using a Deep Neural Network

Code Download: PIXER-master.zip (2296 downloads)

 

Breast cancer histopathological images classification using a hybrid deep neural network

Detail: http://ear.ict.ac.cn/?page_id=1616

Integration of Multimodal Data for Breast Cancer Classification Using a Hybrid Deep Learning Method

Detail: http://ear.ict.ac.cn/?page_id=1663

markerauto1.6.4 version

updates: The “-f” mode will align tilt series according to the given angle file regardless of instrument imprecision (i.e., the “-f” assumes that the platform is quite stable and has little vibration, and would not refine the tilt angles). The default ( without “-f” ) mode will refine the tilt angles and produce refined tilt series that consistent with the transformation.

program: markerauto1.6.4_centos6.5.zip (2705 downloads) , markerauto1.6.4_ubuntu14 (2043 downloads)

Related materials of “DLBI: deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy.”

Related materials of “DLBI: deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy.” DLBI includes three main parts, stochastic simulation, deep neural network and Bayesian inference. There we combine the main idea of SIMBA and DLBI and provide a script to do the analysis of all three parts.

There is a folder includes all files of DLBI and SIMBA, and you can just use the simba.sh to process the data. For further information, please read ReadMe.

Download: DLBI-master.zip (896 downloads)

A Hybrid Convolutional and Recurrent Deep Neural Network for Breast Cancer Histopathological Image Classification

Detail: http://ear.ict.ac.cn/?page_id=1576

Related materials of “Live-cell single molecule-guided Bayesian localization super-resolution microscopy”

Related materials of “Live-cell single molecule-guided Bayesian localization super-resolution microscopy”. These datasets includes two actin structure and one Endoplasmic reticulum structure.

These datasets are owned by Professor Pingyong Xu’s group, and any people who want to use these data should cite the paper “Live-cell single molecule-guided Bayesian localization super-resolution microscopy” and “Rational design of true monomeric and bright photoactivatable fluorescent proteins”. For further information, please contact zhangfa@ict.ac.cn, pyxu@ibp.ac.cn.

Download: real1.tif (1326 downloads) , real2.tif (1275 downloads) , real3.tif (1317 downloads)

 

AuTom-dualx 

AuTom-dualx is a toolkit for fully automatic alignment of dual-axis tilt series with simultaneous reconstruction. It provides global consistent alignment with projection model with different complexity. The default alignment is based on the distortion correction along x, y and z direct. The users are recommended to use this model but a high-level distortion correction is also available by option “-w 2”. Here we give out the pre-compiled exe and test datasets as well as their anticipated results:

dualxmauto(pre-compiled exe):  dualxmauto_ubuntu14 (2409 downloads) , dualxmauto_ubuntu16 (2096 downloads) , dualxmauto_centos6.5 (1811 downloads) , dualxmauto_RedhatEnterprise6.4 (2011 downloads)

dualxmauto(source code): dualxmauto-warp-correction.zip (1402 downloads)

volrec_mltm(pre-compiled exe):  volrec_mltm_ubuntu14 (2730 downloads)

volrec_mltm(source code): volrec_mtlm.tar.gz (2704 downloads) This code has been compiled and run with open MPI 1.8.3 version successfully

Here are the examples demonstrated in the manuscript “Dualxmauto: a toolkit for fully automatic alignment of dual-axis tilt series with simultaneous reconstruction”.To run the examples, module dualxmauto and volrec_mltm is needed.If you extract the tar of testdata, a cmd.txt can be found. Following the cmd.txt you can get the result as in the manuscript or _Anticipated_result.

testdata:  AdhesionBelt.tar.gz (210 downloads) , Centriole.tar.gz (576 downloads) , Simulation.tar.gz (188 downloads)

testdata2: simu1a.mrc (277 downloads) , simu1a.rawtlt (2537 downloads) , simu1b.mrc (257 downloads) , simu1b.rawtlt (2211 downloads) , volume.tlt (2775 downloads)

Anticipated_Result: AdhesionBelt_antiRSLT.tar.gz (193 downloads) , Centriole_antiRSLT.tar.gz (195 downloads) , Simulation_antiRSLT.tar.gz (176 downloads)  

tools: tools.tar.gz (2512 downloads)  

markerauto 1.6.3 version

If the reader run as “markerauto -i V4B_G1_Tilt2.mrc -a V4B_G1_Tilt2.rawtlt -d -1 -o V4B_G1_Tilt2.xf -n V4B_G1_Tilt2.tlt”, markerauto1.6+ will use the old fasion to process the data. If the reader run as “markerauto -i V4B_G1_Tilt2.mrc -a V4B_G1_Tilt2.rawtlt -d -1 -o V4B_G1_Tilt2.xf -n V4B_G1_Tilt2.tlt -t”, markerauto1.6+ will use the Gaussian mixture model based fiducial marker tracking to process the data, which is much fater than the old fashion. The “-t” mode will use GMM-based model and the old fashion will use RANSAC-based model, users can make a execution comparion between these two model. However, because GMM-based model is in its first stage, it is still not so robust. Users are advised that use RANSAC-based model as default and use GMM-model for large field dataset.  

program: markerauto_Centos6.5.tar.gz (2042 downloads) , markerauto_RedHatEnterprise6.4.tar.gz (1886 downloads) , markerauto_Ubuntu14.tar.gz (2848 downloads) , markerauto_Ubuntu16.04.tar.gz (1901 downloads)

test data: test_106.tar.gz , material_data2.tar.gz (1906 downloads) , V4B_G1_Tilt2.tar.gz (7 downloads) , x2adata.tar.gz (6 downloads)

userguide:  markerauto1.6.3_userguide

AuTom beta1.0.1

Automatic Tomography (Au-Tom) is for automatic reconstruction of electron tomography (ET), which covered the pre-processing, alignment and reconstruction of electron tomography. In our package, fiducial marker-based datasets and maker-free datasets are done with totally different subprocess. The presented package has the following characteristics: accurate alignment modules for datasets that contain substantial biological structures but free of fiducial markers;fully automatic alignment modules for datasets that have fiducial markers embedded in; a wide coverage of reconstruction methods with a new iterative reconstruction method that recovers “missing wedge” based on compressed-sensing theory; multi-platform acceleration solutions that support faster iterative algebraic reconstruction. Currently, the markerbasd alignment and reconstruction of AuTom is the mostly well challenged module, while the markerfree alignment still has the limitations of data features. Autom has been built under Red Hat Enterprise 6.4, Cenots 6.5,Ubuntu 14.04 and Ubuntu 16.04. Other systems may not be supported well.

Read the installation guide to learn how to install Autom. You need to 1.download software package of AuTom.  2.Install Library dependencies listed in installation guide: CUDA8, mpich2-1.4.1, gnuplot-5.0.5, libgd-2.1.0 and other dependencies. 3.Click Autom or type “./Autom” in terminal to run the Program. The tutorial and videos (markerbased_video, markerfree_video) show you how to use Autom step by step. Apart from the user iterface, you can also access the modules in the terminal. Please read the user-guides inside the doc package.

 
AuTom beta1.0.1 updates:
1.AuTom now has CTF determination and correction function.
2.AuTom does not need IMOD modules anymore.
3.Reduce the time of reconstruction.
4.Add fast mode to alignment.
5.ICON now has geometry parameters. (For Autom, it handles them automatically, so you don’t need to concern about these parameters in Autom.)
6.ICON now includes a new option called bin, which allows you to bin down a volume. It is useful because you can see the reconstruction result sooner, especially when you want to adjust the parameters of the algorithm.

7.A few bug fixes.

 

If you have any problems or feedback, please submit your question or e-mail us. We really appreciate receiving your advice as soon as possible. E-mail: hanrenmin@gmail.com, zhangfa@ict.ac.cn.

The publication describing AuTom is “Han R, Wan X, Wang Z, et al. AuTom: a novel automatic platform for electron tomography reconstruction[J]. Journal of Structural Biology, 2017, 199(3):196”. Please cite this article in your essay if you use AuTom.

 

AuTom: A novel automatic platform for electron tomography reconstruction (2017 downloads)

 

AutoGDeterm

AutoGDetermV1.0.rar (3135 downloads) AutoGDetermV1.0_UserGuide.docx (2801 downloads)

ICONv1.6.4 & ICONMICv1.0.0

Iterative Compressed-sensing Optimized Non-uniform fast Fourier transform reconstruction (ICON) based on the theory of compressed-sensing and the assumption of sparsity of biological specimen. ICON-GPU_v1.2.8_CentOS64.tar (1479 downloads) ICON-GPU_v1.2.8_Ubuntu64.tar (1855 downloads) ICON-GPU-v1.2.8_UserGuide.pdf (2826 downloads) ICON-MICv1.0.zip (2060 downloads)

dualxmauto

Dual-axis alignemnt and reconstruction result  processed by software dualxmauto. dualx_data.tar.gz (414 downloads)    dualxmauto.tar.gz (1736 downloads)

ET-SPEC(formerly known as ETphantom)

ET-SPEC is a virtual electron microscopy molecular modeling simulation and 3D reconstruction system based on serial block face scanning electron microscope image(SBEM).The package contains installation instruction and a sample date. ET-SPEC.zip (1430 downloads) The source code of ET-SPEC is available. sourcecode.zip (2499 downloads) A Tutorial on getting started with ET-SPEC. Make sure you have installed softwareforET-SPEC.zip (1790 downloads) . Dual-axis nowarp,marker,projection,tracking result generated by ET-SPEC. test_mean_nowarp.tar.gz (1068 downloads) test_mean_nowarp_rot90.tar.gz (1125 downloads) Dual-axis warp,marker,projection,tracking result generated by ET-SPEC. test_mean_warp.tar.gz (765 downloads) test_mean_warp_rot90.tar.gz (443 downloads)

markerauto 1.5.3 version

markerauto_Centos 6.5.tar.gz (2017 downloads) , markerauto_RedHat Enterprise 6.4.tar.gz (2062 downloads) , markerauto_Ubuntu 14.04.tar.gz (2186 downloads) , markerauto_Ubuntu16.04.tar.gz (2102 downloads)

markerauto 1.5.0 version

updates: 1. The initial diameter value can be automatic detected, if the user set the initial input to -1, for example:markerauto -i BBa.st -a BBa.rawtlt -n BBa_new.tlt -o BBa_fin.xf -d -1 2. fixed the bug when proceeding fiducial markers with large diameter. 3. fixed the bug for minimum number of fiducial markers (minimum number: six fiducial markers). markerauto (2034 downloads)

markerauto alpha version

Automatic marker_based alignment module.Material data contains the exe and two small test data (1024×1024). Test_106 contains a test data (with 2048×2048 size). test_106.tar.gz (1105 downloads) material_data_1.tar.gz (543 downloads)

http://v.youku.com/v_show/id_XMTM0ODExMDgyOA==.html

atomalign alpha version

Marker_free alignment module. Material data contains the exe; Mitochondria contains a test data (with 2048×2048 size). mitochondria.tar.gz (1420 downloads) material data2.tar.gz (1643 downloads)

http://v.youku.com/v_show/id_XMTM0ODExMDU3Mg==.html

http://v.youku.com/v_show/id_XMTM0ODExMDY2NA==.html

dualxmauto-warp-correction.zip (1402 downloads) Autom.pdf AuTom: A novel automatic platform for electron tomography reconstruction (2017 downloads) AuTom: A novel automatic platform for electron tomography reconstruction (2017 downloads)