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Thank you so much I finally understood this one day before the final, lol

Well presented .... So Smooth !

The clarity and pace of your lectures is excellent. However, I also appreciate your attention to "smaller" details like adding captions, dividing your videos into chapters, and organizing your content into a playlist. I can imagine you put in a lot of time and work into these extra perks, and I'm really thankful you did so. Cheers from the Netherlands. :)

Thank you a lot!! I learned more in 10 minutes than I learned in a 3 hour class !!! Everything is clear and the slides are vet informative!!

You explain it so well! But i wanna know if there is any reliable software recommend for sequence alignment since i found so many different software online

this is the most simplified video i have found on the internet fir alignemnts thankyou so much kevin, subscribed.

Thank you so much!

thanks a lot. that was super helpful

Very understandable and informative, thank you!

Thanks for your brilliant work!

Wow nice explanation 🙏

Well explained Sir.. Thanks for this video

So it's basically O(2^n)?

Hi, why is V(a,A) = 0.7? I'm still confused on that part. Any explanation is greatly appreciated!

great and simple

Very good videos. Thanks a lot Prof. Yip

雪中送炭的視頻，希望今晚都刷完

哇 講的真的好好

Thanks prof. Yip I am a CUHK student as well

Hi , how do you ensure that by defining likelihood as summing all the possible ancestor states will give the best parameter estimates for a particular ancestor state? I was thinking maybe different ancestor state will have different sets of best parameters.

Hi is this the last section of your modules ? Is it possible that I can get the slides from your modules ?

Thanks a lot for adding new videos, your videos are and very well explained.

wow

nice

You nailed it again Sir!

Sir, you did a really good job in this video. It's been a year since i started learning bioinformatics but I was never sure of what was going on until I came across this video. I decided to comment before even finishing the video because I already got 90 percent of the concept. Thanks a lot.

How is this calculated in bayesian terms? What are the assumed priors? This must be an infuriating probabilistic problem, if we can't even assume the distribution of mutation frequency?

the calculation of ur 2ed table is wrong

Thank you so much! I'm reading a publication about MSA and your videos helped me understand sequence alignment! Very wonderful explanations - by far the best video about sequence alignment on RUclips.

I had little prior knowledge of bioinformatics, but your excellent video made me lose my fear of it, thank you so very much.

Thanks!!! this helps a lot

Precise and well articulated. Perfect!

this is great! Thank you so much

This was super helpful!

will you upload more video about bioinformatics algorithm, such as pca, umap... it's so clear for me to understand, thank you

You explained more in 11 minutes than my professor in 4 weeks, thank you

This was really helpful, and I was able to get a better understanding of this topic. Thank you!

Wow!! My name is Kevin too. So happy to subscribe to your channel🤗🤗 I really need in depth knowledge in Bioinformatics for my masters thesis.

This is an excellent video, thank you very much!

Thanks for watching. Hope it was useful for you.

that is so clear! thank you!

Honestly, this is the best and simplest explanation

excellent video - extremely concise A+ good work

really helpful and easy explanation. thanks :)

how do i know the distance between 2 hub is 1? where is the hint? the math also works when distance between hub go larger and the branches linking hub to B and D shorter

This was very helpful. Subscribed! I look forward to watching more videos. Thank you so much.

Why is it important to generate alignment sequences using protein sequences and not DNA sequences?

Very interesting explanation, Do you have the implementation in Python?

Here, how we calculate distance between AC and B in matrix, i don't understand

I really enjoy your videos! It helps me understand the concepts behind some of the programs and the methods they are using when I am doing analysis