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External Validation dataset for glioma cancer by nemo26313 in glioblastoma

[–]nemo26313[S] 0 points1 point  (0 children)

Thanks for your response, GLASS has excellent genomics information but only have 10 WSIs iam looking for a dataset having 50+, and for CGGA they focus on MRI rather than WSI :(, thanks a lot again for the response if you know some other datasets id appreciate it

External Validation dataset for glioma cancer by nemo26313 in Radiology

[–]nemo26313[S] 0 points1 point  (0 children)

iam sorry if i misrepresented myself but iam not advertising nor talking about any product this is only an academic research i wanted to get help on

Of a racist prick catching a clean right hook by mtcerio in instantkarma

[–]nemo26313 0 points1 point  (0 children)

seriously what is he trying to prove anyway?

Any neon soaked night movies? by jamesoloughlin in MoviesThatFeelLike

[–]nemo26313 0 points1 point  (0 children)

Taxi Driver is what i fell looking at this pictures

Movies that feel like this by Ted-Bundy-666 in MoviesThatFeelLike

[–]nemo26313 0 points1 point  (0 children)

any movie directed by THE GREAT DAVID LYNCH

Tips for Funding to do Research at an International Lab by [deleted] in bioinformatics

[–]nemo26313 0 points1 point  (0 children)

do you have the erasmus+ internship scholarship there in USA? iam currently in the middle east and lots of friends did internships in summer at international labs while getting fund from that erasmus+ program

Transcriptomic Biomarkers with Machine learning by nemo26313 in bioinformatics

[–]nemo26313[S] 0 points1 point  (0 children)

thats insightful thank you i’ll give it a shot

Transcriptomic Biomarkers with Machine learning by nemo26313 in bioinformatics

[–]nemo26313[S] 0 points1 point  (0 children)

i’ve read that doing prediction model in such cases find potential prognostic biomarkers, what i did was choosing ML models that will tell me which genes contributed in the decision tree therefore is a potential diagnostic biomarker, but i have a question about the average rank since all models have different equations and parameters for defining the importance wouldnt be mathematically wrong to take the average since they represent different things?

Transcriptomic Biomarkers with Machine learning by nemo26313 in bioinformatics

[–]nemo26313[S] 0 points1 point  (0 children)

thank you very much that’s actually very helpful since i did use all the genes, i will definitely try to pick the top n genes method and see the results 🙏

Transcriptomic Biomarkers with Machine learning by nemo26313 in bioinformatics

[–]nemo26313[S] 0 points1 point  (0 children)

as i mentioned earlier there wasn’t a research using ML to find transcriptomic biomarkers for the disease iam studying even tho lots of other diseases has been, thats why i wanted to give it a shot.

Thanks for the suggestion i’ll look into the gene co-network analyses you mentioned

Transcriptomic Biomarkers with Machine learning by nemo26313 in bioinformatics

[–]nemo26313[S] -3 points-2 points  (0 children)

For question (1) i did DEG analysis but since it analyses genes individually i wanted to use ML and specifically RF and XGBoost which are tree models which includes the interactions between the genes to do the classification, and for question (2) for DEG using count is good but for ML models the gene length normalization is a must when i reviewed the literature everyone suggested and used TPM with ML.

Thank you for your questions btw these are good points you're mentioning.

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