- Видео 77
- Просмотров 102 005
Ahmet Sacan
Добавлен 9 окт 2011
Видео
Introduction to Computers for Beginner Matlab Programmers .v183
Просмотров 1,3 тыс.4 года назад
Introduction to Computers for Beginner Matlab Programmers .v183
Writing your first Matlab function: aplusb .v191
Просмотров 5314 года назад
Writing your first Matlab function: aplusb .v191
Using Matlab Online v191
Просмотров 3424 года назад
If you do not have the Matlab program installed on your computer or for some reason you don't have access to the program, you can use Matlab Online as an alternative.
Suffix Trees for Next-Gen Sequencing .v182
Просмотров 3474 года назад
Suffix Trees for Next-Gen Sequencing .v182
Sequence Local Alignment and Homology Search Statistics
Просмотров 4984 года назад
Sequence Local Alignment and Homology Search Statistics
Sequence Alignment using Dynamic Programming Algorithm
Просмотров 9 тыс.4 года назад
Sequence Alignment using Dynamic Programming Algorithm
Sequence Homology Search Algorithm - BLAST
Просмотров 9255 лет назад
Sequence Homology Search Algorithm - BLAST
Prosite patters follow most of regular expressions.
What is "residue" here?
I’m also wondering
When do we need to use this procedure and when the k-mers method?
I've watched several tutorials explaining sequence alignment and this is the best one.
Very good explanations.
You're the best explainer I ever come across. Thanks!
hiçbir hintliden aksanlarından dolayı anlayamamıştım, sizlerin aksanız muhteşem teşşekkürler hocam
brilliant explanation
Thanku😄
THx u Sir! This video gives me a clear view!
incredible visualization and explanation, thanks a lot
the work on X-rays in discovering the double helix structure was contributed by Rosalind Franklin. That story of credit not given to her for her contribution is so well known by now, I feel like not mentioning her is almost a parody at this point...
perfect explanation right at the point
Thank you. This was very helpful. I didn't know how I should apply genetic algorithm in multiple alignment. Your explanation was simple yet useful.
Really helpful. very detailed analysis and explanation. Thank you.
Great explanation! Thanks
thank you !
sir we need more videos sir for machine learning
Fisher’s linear discriminant video plz sir
well done
thanks alot
Your explanation is wonderful👍👍👍
Great review! Is PCA video available?
Yes. ruclips.net/video/V_BFkt6F3Z4/видео.html
dünyanın sanki senin çekeceğin ingilizce videoya ihtiyacı mı var tr çek de ülkene bi faydan olsun
Such a perfect explanation, everything is so logical and graphics really help to understand it better! Thanks a lot!
Detailed explanation. Very good! Thank you!!
How I wish I can like this video a million times! Thank you for the hard work and nice explanation
I like your explanation, thank you so much God bless you
with quadratic discrimination analysis, I'm getting error saying my covariance matrix can't be singular. What does this mean? Amazing video by the way👍
Superb explanation! This was roughly my intuition when I studied the algorithm but it's good to see it summarized and eloquently explained.
Well, at least some use comes of it. Wonderful
nice to meeet you! are you living in Turkey? if yes, where? are you open to private lessons? about these type of theories
this video is so helpful , thank you very much. i think it will be better if you put the pdf or the file that you are using it will allow us to revise it easier
amazing video talking about the computational complexity! very helpful!
19:2
fantastic video. thanks a lot
Thank you
The absolute best explanation
Thank you so much, Sir
Fantastic overview. I do feel that nanopore sequencing should have been included in the next gen conversation, though it breaks from the pattern of wanting massively parallel analyses
Hi. Could you share the code?
Very Informative video sir, really helpful. Thanks a lot for making and uploading.
This is great Ahmet thank you.
Great explanations, thanks
Man you teach beautifully.
That was easy to understand. Thank you so much.
Amazing video! Soo helpful, thank you so much. Videolarınız için çok çok teşekkürler hocam, çok faydasını gördüm..
can you share the code pls? thnx
Hello. Did you get the code??
Thanks, very clearly explained!
Well explained.. Thank you
Nice explanation but @34:46, in the expression of g(x) the first term should be (miu)^t / (sigma)^2 instead of (miu)^t /2* (sigma)^2. please check
Fantastic introduction to gradient descent, thank you!