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These courses are amazing! Thank you for this well-reasoned and thorough guide to mathematical modeling in biology

Thank you for this course. I am confident I will learn a lot from you - you appear to be an exceptional professor! Thank you again

These lectures are great!

Thank you Sir❤

Thank You

Thank you very much Sir

Thank you very much, you made the topic very interesting and easy Sir!

Thank you sir This is so valuable

Thank u

Thanks Sir

Very detailed and simplified explanation❤ Thank you Professor

where are you sir

did anyone make a paper of this model?

very nice sir

nice

It was amazing! Thanks a ton sir. :)

In future i wanaa i will work on this topic.....

Thank you Prof. Biplab sir

Thank you very much sir

thank u sir u are a life saver

Thank you

Thank you 🙏

Excellent explanation !!!!

Thank you sir... Can i get a one lecture modeling on blood flow?

dear sir, please add the codes of the discussed graphs. Thanks

Sir, please arrange your all videos in order. thanks give them proper numbering.

Great lecture. Thank you sir

Sir, can you recommend reference book for this topic?

Very useful sir

Sir jee very nice

Wow this is an amazing explanation, thank you so much

Thanks sir ...

thankyou so much sir. Very good explanation & easy to understand.

you are literally the BEST professor. thanks for explaining this so so clearly.

Thanks professor ❤️

Thank you sir

Awesome!!

Great talk!

I even didn't open up the Calculus to understand the ODE. Your explanations was enough me to understand that. However, I know that I should open it to deepen my knowledge about the equations more. Thank you very much. It would be better (for me) if you give examples from ecology, microbiology because I am not very well at molecular biology (or biochemistry, physical chemistry). Thank you again.

Thank you sir 🙏

Thank you sir 🙏

Helo

Thank you 🙏🏻 very helpful indeed

Great lecture Dr. Bose. Regarding the assumptions about ODE models. Homogeneity: is the reason for this assumption that it reduces the number of independent variables to 1... namely time? We can just think of the system evolving in time rather than in both time and space? For the second assumption: that the population is large - is this assumption made so that the ODEs are continuous and differentiable for all times? Basically so that the curves aren't spikey/cuspy or shaped like step functions? Thanks again, very informative.

It seems that Dr. Biplap recorded this and the previous modules altogether because of that he is sweating. Thank you very much!

"we'll understand how novel features come out of the dynamics of this transcriptional network or cell signaling system in terms of mathematical models. Mathematical biology is becoming essential every day as biology is becoming more and more quantitative. Dynamical models are giving new dimension of understanding of biology as we try to capture the dynamics by experiment and we try to understand the mechanism behind those phenomena in terms of mathematical models." Amazing introduction!

Sir I want to know ,when once infection increase and it reach to the top the it will definitely slow down then how we will plot the slow down with this ODE model.

Sir, at time 9:31min of lecture how the Phase portrait of dy/dt=-y is drawn for m=0 and m>0 cases? Can you please explain? Thank You.

Thank you, sir!