using machine learning regards to ribo-seq data sets

Question

[zizigolu]

Hey friends,

I want to inference GRN from high throughout sequencing data but I could not find any practical papers just found some papers explaining this field theoretically. There are many papers for microarray and I found something about chip-seq and k-mer but I could not find an aspiration for ribo-seq. Do you have any idea or suggestion please. You suppose I am going to inference GRN from ribo-seq data sets. Thank you very much

[PoGibas]

What is GRN?

[Michael]

Gene-regulatory network?

[zizigolu]

Yeah the same gene regulatory network I mean

[Michael]

I think it is not found because it isn't possible or hasn't been figured out yet. A gene regulatory network is a directed graph model of causal regulatory relationships between genes, e.g. a transcription factor and a target gene. Ribosome sequencing detects transcript regions with bound ribosomes. I am sure one can do a lot with ribo-seq (determining RBS, alternative translation start sites, etc.), but which other interaction partner could be inferred by this approach?

Unless you could interpret the binding peaks quantitatively and not only qualitatively, you do not even have a chance of doing some sort of correlation network. And I am not sure if it is valid to interpret the number of sites or the number of reads per transcript as an quantitative equivalent of translational efficiency. If the data is quantitative, it would be an interesting task to integrate them with GRN from other sources. I think that this data-type is very new and warrants further investigation.

[zizigolu]

Thanks a lot Michael to clarifying the subject for me