I am surprised how much effort he has made. I am Japanese and as an Asian, I know how hard it is to learn English to his level. Not only that, he is good at data science in addition to biology. Things never end there. His videos are really well-made. I know how difficult to make a quality video because I once tried to make videos but they were just scraps.
@@DataProfessor Thanks, data professor! I recently obtained my PhD degree in theoretical astrophysics, and I'm interested in anti-aging / anti-cancer drug discovery. I don't have a background in biology, while I find your videos super helpful. I used your machine learning scripts from the video "Python for Bioinformatics - Drug Discovery Using Machine Learning and Data Analysis", trying to find compounds that may have potential to inhibit mtor (target CHEMBL2842). The random forest model using 4727 training examples achieved Coefficient of determination (R^2): 0.90 and Mean squared error (MSE): 0.18. In app.py, I had to use -Xms1G -Xmx1G instead of -Xms2G -Xmx2G to generate descriptors_output.csv for just my input molecules, otherwise I'm getting a list of all 4727 compounds in the app. As a test, I run app.py, input CHEMBL413 (Rapamycin) and CHEMBL295124 (Berberine). I got predicted pIC50 = 7.06 and 6.43, respectively. Since these are well known mtor inhibitors, the result looks reasonable. The weird thing happens when I took your original example input in Part VI, example_acetylcholinesterase.txt, which includes 5 candidates AChE inhibitors (CHEMBL133897, CHEMBL336398, CHEMBL131588, CHEMBL130628, CHEMBL130478). And surprisingly I got predicted pIC50 for mtor inhibition in the range 6.5-6.8. I wouldn't expect AChE inhibitors would also inhibit mtor efficiently. Did I do something wrong? It seems that the feature representation is super important in QSAR models. So far we have been using 881 molecular fingerprints. I wonder if we were to use graph neural networks to learn the feature representation of molecules, instead of using hard coded fingerprint features, would the machine learning model achieve better performance?
Thanx a lot professor for this amazing content, I'm studying data science and we have a project that is a "model design platform" and your channel has been amazingly helpful. Your efforts are greatly appreciated.
Hi, professor, I selected MS data Science from FAST NUCES ISLAMABAD, Pakistan, and working on Computational drug discovery it's the start of my research journey in bioinformatics for data science. As this university is the NUCES so, there is no bioinformatics teacher to guide me Your video always help me in understanding bioinformatics knowlgede.
Excellent lecture.. Straight to the point. Thank you for it. It lightened some information gaps that I had before listening to this. I saved it and I might need to follow it again. This will help me to improve my articles and my phd thesis on drug-drug interactions.
Thank you Prof. I was able to run your codes (chembl research work) in jupyter notebook using multiple environments. I modified the coding so I could do eveything in jupyter without using Google colab. Thank you very much for your contribution to knowledge. I'm a Nigerian lecturer currently doing my PhD in Chiang mai Thailand
This content is awesome, thank you so much for sharing! I recently joined a Gene Silencing company as a Machine Learning Engineer, but I have no biological background. This is immensely helpful! Thank you so much for sharing this video! Are you planning on sharing the rest of the lectures?
That is awesome! I actually have related hour long lectures: - How to build bioinformatics tools ua-cam.com/video/LHM0Couv0w4/v-deo.html - Data science for bioinformatics ua-cam.com/video/3AqQn94KVZU/v-deo.html - AMA about bioinformaitcs ua-cam.com/video/BbOV33C5oJg/v-deo.html - 6-part series on Bioinformatics from Scratch ua-cam.com/video/plVLRashaA8/v-deo.html
Thanks for the great material professor. I’m planning to pursue my postgraduate studies in this field, and I have learned a lot with your videos. I have one question, What do you think about graph neural networks applied to drug discovery?, Do you think that this new approach will foster this field?
That's a great question, I think it's a great idea, it could be potentially used for representing molecules as interconnected graphs where atoms are nodes and bonds are edges. This could also be applied for biological networks at the systems biology level as well.
It is always amazing to view Data Professor Learning-centered sessions. Sir, could you please make some separate videos for Molecular Docking and Dynamics using python machine learning and colab.
Hi, the easiest way is to compile a dataset of receptor and ligand pairs along with their respective binding energy. Then apply ML to make the prediction. Instead of binding energy, you could find experimental binding values such as the binding KD or KA (dissociation and association) as well. Additionally, instead of binding, you could predict the inhibition value such as IC50 or pIC50 (the log form). I've made the Bioinformatics video series showing how you can compile your own dataset from the ChEMBL database here ua-cam.com/video/plVLRashaA8/v-deo.html Hope this helps.
Amazing video as always. Could you kindly make a video on obtaining data from databases and then merging meaningful data from multiple databases? Im currently trying to combine IC50 data for a set of compounds from CHEMBL with hepatotoxicity data from another database but failing to do so. Are these such databases where multiple ADMET properties for compounds against a protein are given? with enough data to build models to predict multiple properties at once
Awesome, sir. I am interested on bioinformatics and want to research on this field but I don't have knowledge of programming language. So, would you plz recommend me which language should I start with ?
I have 2 recommendations, choose 1: Python or R. Please watch the following videos for more info: 1. Python vs R ua-cam.com/video/zyh2HU1efo4/v-deo.html 2. Python 101 playlist ua-cam.com/video/TYPwkfhpwKU/v-deo.html 3. R 101 playlist ua-cam.com/video/vmAjWcAKUqQ/v-deo.html I use both R and Python for my research. The decision is primarily because my students either uses R or Python. Both have cheminformatics related libraries and packages, which are the main reason for using either language. Select a library or package that you think answers your needs. Hope this helps.
Hello,😅 I came across this channel and i was never really interested data science. But after watching this video, i want to seek a career in this field. What can i do to get started?
One can use GANs for generating new molecules. If one wants to generate molecular decoys, there’s the DUD-E tool by the Shoichet group. The Reymond group also has done some extensive work in computational enumerating new molecules in a de novo fashion.
@@DataProfessor Thanks for your valuable information, My PhD supervisors suggest to take GANs as my PhD subject and they suggest using GANs for drug discovery ? Is this a good subject for PhD, especially i have low knowledge in cheminformatics and bioinformatics. Would you recommend using GANs to create a synthetic dataset as PhD subject or GANs becomes so an interesting topic for only large companies.
Hello, thank you for your videos, Can I ask you for an advice please? how would be the best way to get in to drug discovery part of R&D pharmaceutical? I am currently a pharmacist pharmD, Take a course in Ml and data science? Or chemoinformatics? I realy get confuse what to do and what to learn or study and how would be the short-cut and best way for it?
Prof., Thanks for this lecture, can you please help me with a lecture on cmputatutional drug design using plant as a case study ? . thaks for your anticipated cooperation!.
Thank your for this amazing video. Ia have twe questions: 1. What software can we use to enumerate (going from A to A1, A2, A3...)? 2. Do you have a UA-cam explaining how to get the enumerations?
Hi, there are several ways of doing this. One of many would be AutoGrow which enumerates molecule in the confinement of a protein binding cavity. There’s also one from KNIME www.knime.com/knime-applications/chemical-library-enumeration
Hello, I am learning a great deal from your videos. I was just wondering is it possible to get the lecture slide as pdf and also your drawings and explanation in the form of pdf, perhaps by a github link?
Professor, this video is so insightful. I have subscribed to your UA-cam channel, and I can't wait to feed on more contents on your channel. I have a few questions, sir. 1. What do you think is the future of natural-product based drug discovery? 2. What skills and knowledge should I acquire to better prepare me for graduate studies in drug discovery and development? I'm applying to different schools and I hope to study wide even before I get admitted. I believe it will boost my application and prepare me better for graduate school. Thank you so much sir.
Hallo Prof, I am currently pursuing BSc Genomic and Molecular Science. I have a lot of questions I would like to ask you sir as your methods of teaching is more elaborate. How can I contact you?
@@DataProfessor your students are so blessed to have you. Anyway, thank you for sharing this. This is a really great help for us who search for resources and consultants online.
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I am surprised how much effort he has made. I am Japanese and as an Asian, I know how hard it is to learn English to his level. Not only that, he is good at data science in addition to biology. Things never end there. His videos are really well-made. I know how difficult to make a quality video because I once tried to make videos but they were just scraps.
127 RESEARCH ARTICLES?!?! You are a beast Prof! I’ll be back to watch this entirely this weekend. LEGENDARY video!
Thanks Nicholas, all credit goes to my students and colleagues, they are the true heroes! 😊
You both make legendary videos :)
UA-cam give this Professor the views that he deserves
Thanks, prof for the lecture
Hey thanks for the big support!
Incredible explanation, thank you very much sir. The fact that resources like this are available to everyone on youtube amazes me.
This is really nice. Now I can fully understand data science for bioinformatics. Thank you.
Data Professor is really good at explaining technical concepts in a simple way
Thanks, glad you think so, this means a lot :)
@@DataProfessor Thanks, data professor! I recently obtained my PhD degree in theoretical astrophysics, and I'm interested in anti-aging / anti-cancer drug discovery. I don't have a background in biology, while I find your videos super helpful. I used your machine learning scripts from the video "Python for Bioinformatics - Drug Discovery Using Machine Learning and Data Analysis", trying to find compounds that may have potential to inhibit mtor (target CHEMBL2842). The random forest model using 4727 training examples achieved Coefficient of determination (R^2): 0.90 and Mean squared error (MSE): 0.18. In app.py, I had to use -Xms1G -Xmx1G instead of -Xms2G -Xmx2G to generate descriptors_output.csv for just my input molecules, otherwise I'm getting a list of all 4727 compounds in the app. As a test, I run app.py, input CHEMBL413 (Rapamycin) and CHEMBL295124 (Berberine). I got predicted pIC50 = 7.06 and 6.43, respectively. Since these are well known mtor inhibitors, the result looks reasonable. The weird thing happens when I took your original example input in Part VI, example_acetylcholinesterase.txt, which includes 5 candidates AChE inhibitors (CHEMBL133897, CHEMBL336398, CHEMBL131588, CHEMBL130628, CHEMBL130478). And surprisingly I got predicted pIC50 for mtor inhibition in the range 6.5-6.8. I wouldn't expect AChE inhibitors would also inhibit mtor efficiently. Did I do something wrong?
It seems that the feature representation is super important in QSAR models. So far we have been using 881 molecular fingerprints. I wonder if we were to use graph neural networks to learn the feature representation of molecules, instead of using hard coded fingerprint features, would the machine learning model achieve better performance?
This is wild, looking into getting a master's in Bioinformatics so this is a very interesting intro!
Awesome! Lots of potential areas to explore in the field.
Love your videos sir learnt a lot from you. You deserve more viewership in my opinion. Thanks a lot for the hard work.
Thanks for the kind words! :)
ขอบคุณมากๆนะคะอาจารย์ หนูกำลังสนใจเรียนนี้เลยค่ะ ช่วยให้เขาใจได้เยอะเลยค่ะ
Thanx a lot professor for this amazing content, I'm studying data science and we have a project that is a "model design platform" and your channel has been amazingly helpful. Your efforts are greatly appreciated.
Hi, professor, I selected MS data Science from FAST NUCES ISLAMABAD, Pakistan, and working on Computational drug discovery it's the start of my research journey in bioinformatics for data science. As this university is the NUCES so, there is no bioinformatics teacher to guide me Your video always help me in understanding bioinformatics knowlgede.
Excellent lecture.. Straight to the point. Thank you for it. It lightened some information gaps that I had before listening to this. I saved it and I might need to follow it again. This will help me to improve my articles and my phd thesis on drug-drug interactions.
Thank you Prof. I was able to run your codes (chembl research work) in jupyter notebook using multiple environments. I modified the coding so I could do eveything in jupyter without using Google colab. Thank you very much for your contribution to knowledge. I'm a Nigerian lecturer currently doing my PhD in Chiang mai Thailand
Sawatdee krub, glad to hear that the video was helpful and good luck in your PhD endeavors :)
What a brilliant presentation. Kudos to you
Good topics to understand that explain step by step
Love the way teaching
Great to learn
This content is awesome, thank you so much for sharing! I recently joined a Gene Silencing company as a Machine Learning Engineer, but I have no biological background. This is immensely helpful! Thank you so much for sharing this video! Are you planning on sharing the rest of the lectures?
That is awesome! I actually have related hour long lectures:
- How to build bioinformatics tools ua-cam.com/video/LHM0Couv0w4/v-deo.html
- Data science for bioinformatics ua-cam.com/video/3AqQn94KVZU/v-deo.html
- AMA about bioinformaitcs ua-cam.com/video/BbOV33C5oJg/v-deo.html
- 6-part series on Bioinformatics from Scratch ua-cam.com/video/plVLRashaA8/v-deo.html
Thanks for the great material professor. I’m planning to pursue my postgraduate studies in this field, and I have learned a lot with your videos. I have one question, What do you think about graph neural networks applied to drug discovery?, Do you think that this new approach will foster this field?
That's a great question, I think it's a great idea, it could be potentially used for representing molecules as interconnected graphs where atoms are nodes and bonds are edges. This could also be applied for biological networks at the systems biology level as well.
Could you make a tutorial video about de novo new compounds by applying machine learning, Professor? I think it is a very interesting topic.
It all makes sense
Thank you Professor
You’re welcome!
Thanks for sharing. Inspiring me feeling back to the old place again
Thanks krub Boyd, Glad to hear that! You're also doing great things in the data space with your contents 😊
Your video is really great. But the background noise was slightly disturbing.
Please, can you share the slide?
Watching this course and planning on integrating in silico drug discovery in my next project. Thank you, Professor!
It is always amazing to view Data Professor Learning-centered sessions. Sir, could you please make some separate videos for Molecular Docking and Dynamics using python machine learning and colab.
Great idea, will try to simplify as much as possible so that it also appeals to the general data and machine learning community 😊
@@DataProfessor thank you sir. You are an inspiration 👍
Thanks!
Thanks for the support!
Thank you so much for such a brilliant video!
I have a request. Can I get notes and slides for this video?
Very informative and enjoyable!! Thank you for putting this video up. Best wishes.
Thanks!
Thanks sooo much for this introduction to computational drug discovery. please prof how can someone have access to BioCurator
Your teaching methods are top notch 👌🏾
I appreciate that!
Fascinating! Thx for sharing.
Glad you enjoyed it!
best 2:30 Hours ... Thank you professor
Thanks, glad to hear that :)
thank you so much, that is awesome
This is so helpful! Thanks a lot professor :)
You're very welcome!
Had a great lecture on that day. Sir
Thank you, glad to hear that 😊
thanks professor! I learn more here than in my university:')
thanks, Prof., really need you to explain to us how the receptor and ligand interaction and how to estimate binding energy via ML?
Hi, the easiest way is to compile a dataset of receptor and ligand pairs along with their respective binding energy. Then apply ML to make the prediction. Instead of binding energy, you could find experimental binding values such as the binding KD or KA (dissociation and association) as well. Additionally, instead of binding, you could predict the inhibition value such as IC50 or pIC50 (the log form). I've made the Bioinformatics video series showing how you can compile your own dataset from the ChEMBL database here ua-cam.com/video/plVLRashaA8/v-deo.html
Hope this helps.
@@DataProfessor thank prof. If I have a doubt, I will contact you
Amazing video as always. Could you kindly make a video on obtaining data from databases and then merging meaningful data from multiple databases?
Im currently trying to combine IC50 data for a set of compounds from CHEMBL with hepatotoxicity data from another database but failing to do so. Are these such databases where multiple ADMET properties for compounds against a protein are given? with enough data to build models to predict multiple properties at once
Awesome, sir. I am interested on bioinformatics and want to research on this field but I don't have knowledge of programming language. So, would you plz recommend me which language should I start with ?
I have 2 recommendations, choose 1: Python or R. Please watch the following videos for more info:
1. Python vs R ua-cam.com/video/zyh2HU1efo4/v-deo.html
2. Python 101 playlist ua-cam.com/video/TYPwkfhpwKU/v-deo.html
3. R 101 playlist ua-cam.com/video/vmAjWcAKUqQ/v-deo.html
I use both R and Python for my research. The decision is primarily because my students either uses R or Python. Both have cheminformatics related libraries and packages, which are the main reason for using either language. Select a library or package that you think answers your needs.
Hope this helps.
@@DataProfessor Thanks, sir. Is it necessary to learn C/C++ in relation to bioinformatics/chemoinformatics study?
Hello,😅 I came across this channel and i was never really interested data science. But after watching this video, i want to seek a career in this field. What can i do to get started?
Excellent presentation very useful. Congratulations.
Prof. Pls are we able to get the slide for this video? Thank you
Awesome and resourcefull lecture.
Many thanks!
which software can i make use of for docking
This is amazing content! Thank you Professor!
Thanks for a helpful video!
Do you have any recommendation for molecular generators, which automatically expand the chemical space to search?
One can use GANs for generating new molecules. If one wants to generate molecular decoys, there’s the DUD-E tool by the Shoichet group. The Reymond group also has done some extensive work in computational enumerating new molecules in a de novo fashion.
@@DataProfessor thanks a ton! I'm gonna look into it.
@@DataProfessor Thanks for your valuable information, My PhD supervisors suggest to take GANs as my PhD subject and they suggest using GANs for drug discovery ? Is this a good subject for PhD, especially i have low knowledge in cheminformatics and bioinformatics. Would you recommend using GANs to create a synthetic dataset as PhD subject or GANs becomes so an interesting topic for only large companies.
@@ahmedyamany5065 It’s an interesting topic that is at the fore front of the field, both for academia and pharma industry.
Simple, Thank you.
Hello,
thank you for your videos,
Can I ask you for an advice please?
how would be the best way to get in to drug discovery part of R&D pharmaceutical? I am currently a pharmacist pharmD, Take a course in Ml and data science? Or chemoinformatics? I realy get confuse what to do and what to learn or study and how would be the short-cut and best way for it?
Prof., Thanks for this lecture, can you please help me with a lecture on cmputatutional drug design using plant as a case study ? . thaks for your anticipated cooperation!.
Thanks man!!
Good job bro 👌👌👌
Thanks for tuning in!
Can u pl make a video regarding ligand based pharmacophore modeling.
Thx Professor, you are the best :)
Is there a possible to make money out of this? What is possible application for earning potential? I'm too naive to know right now but want to learn .
Thanks for the great post. Does one need a PhD to start a career as a computational drug discovery scientist?
How do I scan a large number of molecules for the Lipinski rule at once?
Can the protein be genes instead?
Is python fast enough. C++/ fortran? Parallel programming?
Very informative! One question, how do you filter 'salt'?
What are the courses i should know before watching this video ?
Thank your for this amazing video.
Ia have twe questions:
1. What software can we use to enumerate (going from A to A1, A2, A3...)?
2. Do you have a UA-cam explaining how to get the enumerations?
Hi, there are several ways of doing this. One of many would be AutoGrow which enumerates molecule in the confinement of a protein binding cavity. There’s also one from KNIME www.knime.com/knime-applications/chemical-library-enumeration
@@DataProfessor thanks for your quick answer. I'm going to review the AutoGrow and KNIME documentation.
Hello, I am learning a great deal from your videos. I was just wondering is it possible to get the lecture slide as pdf and also your drawings and explanation in the form of pdf, perhaps by a github link?
Professor, this video is so insightful. I have subscribed to your UA-cam channel, and I can't wait to feed on more contents on your channel.
I have a few questions, sir.
1. What do you think is the future of natural-product based drug discovery?
2. What skills and knowledge should I acquire to better prepare me for graduate studies in drug discovery and development?
I'm applying to different schools and I hope to study wide even before I get admitted. I believe it will boost my application and prepare me better for graduate school.
Thank you so much sir.
Hallo Prof, I am currently pursuing BSc Genomic and Molecular Science. I have a lot of questions I would like to ask you sir as your methods of teaching is more elaborate. How can I contact you?
41:00 inhibit estrogen? Aromatase
Wow, this is super exciting!! :)
hello professor, I want to ask if I could apply for an internship in your laboratory
I love you professor
Hey thanks!
how to join your live session sir? Is this a separate event or is it for those who are channel member?
Hi, it's actually recorded from a class I taught at the university.
@@DataProfessor your students are so blessed to have you. Anyway, thank you for sharing this. This is a really great help for us who search for resources and consultants online.
Very helpful lecture sir. Is there any way I can connect with you?
You can find me on Twitter and LinkedIn. Details in the video description and also sign up to my newsletter.
Jack wasnt paying attention
it is python project or not
why there is no sound in this video?
Hi, I’ve checked again and the audio works normally
I want to work with you. I am passionate about Bioinformatics.
Awesome, I'll soon have some public datasets that the entire community can contribute to. Soon.
@@DataProfessor I would like to do a PhD in Computational Biology and Bioinformatics. Can you mentor me?
why do you share your knowledge?
sir your video is not clear plesase try to make it clearer