Visit brilliant.org/OMGenomics/ to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription.

Loving this channel! Keep it up! Could you cover machine learning in genomics?

Love to see you again, thanks for the review!

Thank you for your work!

Wonderful video✌️ Nice explanation of what morden biology looks like. Very excited to contribute more in the field.

Thanks for share your enthusiast!

Thanks.

Can you please do some videos on how to visualise somatic variants using plots and graphs ? thank you !! Or if anyone has any recommendations please let me know.

Hi Maria I’m a huge fan of your videos

What is best place to do a whole genome sequencing in your opinion?

I think the alignment tools should be renewed after pan genome published~

6:20 pangenomes

Hello I’m a molecular biology student and I would like to know if it’s possible to continue my phd studies in computational biology or bioinformatics. I don’t like working in lab. Do I need to get another master’s degree? (I already have an MS in Molecular biology)

Myself is currently working on All of Us analysis, I would say phenotype data is probably the worst thing to deal with…

@PennytheBALLstar13

2 жыл бұрын

Why is that?

@user-xd1dc3od1b

2 жыл бұрын

It’s laboring to collect in the greenhouse…Is that what you are talking about?

@taotaotan5671

2 жыл бұрын

@@PennytheBALLstar13 Diseases are complicated and usually has a hierarchical structure, e.g. diabetes or leukemia may have many subtypes, then which one is the one you want to study? Which sample should you select as control group? These aren’t typical skills that a bioinformatician will have. There are other things to consider, e.g. what if patients' survey data is not consistent with electronic medical records. How to query and clean the messy database? and more... Anyway, realistic phenotypes are much more than 0 and 1 encoding.

@taotaotan5671

2 жыл бұрын

@@user-xd1dc3od1b No... I meant querying and parsing realistic phenotype data is generally a very challenging task for a bioinformatician, given the complication of diseases, and messiness of data.