source code for context-specific TF co-association analysis in ‘Architecture of the human regulatory network derived from ENCODE data’

Q:
I have benefited a lot from you work entitled ‘Architecture of the human regulatory network derived from ENCODE data’ and I want to use the framework you developed for context-specific TF co-association analysis. However, I can’t find the source code at your given address http://code.google.com/p/tf-co-association/. Do you have the replaced address to share the source code for that?

A:
Is this what you are looking for?
https://code.google.com/archive/p/tf-coassociation/source/default/source

Regulatory Genetic network AND DSPN

Q:
I am studying your publication in Science (Comprehensive functional genomic resource and integrative model for the human brain, Science 362,1266(2018) with great interest. As a quantitative geneticist, I found it very relevant to the study of complex genetic traits. Therefore, I am writing this note to request your assistance inorder get your software/algorithm for Regulatory Genetic Network modeling and Integrative deep learning model (DSPN) so that we could implement them at NIH supercomputer system and conduct some integrative genomic modeling work in the area of brain/neuropsychiatry.

A:
Best to see resource.psychencode.org. Specifically — you can find the matlab codes "7. Matlab code and formatted data for
the DSPN" on http://resource.psychencode.org/

Request for the supplementary data of the ENCODE paper

Q:
My projects focus on exploring the mechanisms of gene regulation. I recently read the ENCODE paper (Architecture of the human regulatory network derived from ENCODE data, 2012) again and realized that the supplementary data will greatly help us to refine our results.

Unfortunately, I found that all the files have been achieved. Both of the following sites can’t be reached. I am writing to ask if there are any other ways to access the files. Thank you very much for your time. I am looking forward to hearing from you.

http://encodenets.gersteinlab.org
http://archive.gersteinlab.org/proj/encodenetsold/

A:
http://encodenets.gersteinlab.org
should be up shortly

Inquiry about STRESS

Q:
I am writing this e-mail to inquire about STRESS software.

We have learned from your paper (Structure 2016,24:826-837)
that STRESS software can be used for identifying allosteric pockets.
We are interested in using the software for our drug discovery research.
We will perform evaluation of the software for a start.

Will you allow us to use STRESS software for the purpose of our
commercial drug discovery project free of charge?

As this is an urgent project, we would highly appreciate if you could
reply soon.

A:
see license at https://sites.gersteinlab.org/permissions/

HiC-Spector data

Q:
We have read with much interest your article about the HiC-Spector method.
We are currently working on a method that we hope will help identify
conserved features across different HiC-maps. As the problem we are studying
and the one tackled in your article are closely related, we think it would
be useful for us to test our method using your data set as the ground truth.
We kindly ask whether you would be able to provide us with the HiC maps used
in the article for this purpose.

A:
https://github.com/gersteinlab/HiC-spector/blob/master/data/readme_data