How to build a protein structure prediction app in Python using ESMFold and Streamlit

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  • Опубликовано: 1 окт 2024
  • In this video, we'll build a web app for predicting the protein structure in Python. Briefly, ESMFold is used as the protein structure prediction engine while Streamlit is used as the web framework. This app will be built in a little over 60 lines of code.
    🐙 Code github.com/dat...
    🕹️ Demo app esmfold.stream...
    App built using the Streamlit app starter kit
    📖 Blog blog.streamlit...
    📦 App template github.com/str...
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Комментарии • 34

  • @adityavardhanjain
    @adityavardhanjain 11 месяцев назад +4

    the api referenced is getting an authentication error. What can an alternative be?

  • @kevinalexis9886
    @kevinalexis9886 Год назад +9

    Please do more Bionformatics videos, your playlist is awesome!

  • @qaziacademy3048
    @qaziacademy3048 Год назад +3

    Hi Sir. I m watching ur videos and r very good informative videos. Please guide me in my PhD word. My research work is related to Prediction of AntiCancer Peptides using Deep Learning. I want to extract features through Natural Language Processing Techniques. Please guide me how to extract via NLP.. Thanks Sir

    • @ЛидияШишина-у5ч
      @ЛидияШишина-у5ч Год назад +1

      Hi, you need to get embeddings from natural language model like Bert by tokenizer :sequence_w_spaces = ' '.join(list(sequence))
      encoded_input = tokenizer(
      sequence_w_spaces,
      truncation=True,
      max_length=len_seq_limit,
      padding='max_length',
      return_tensors='pt').to(config.device)
      output = model(**encoded_input)
      output_hidden = output['last_hidden_state'][:,0][0].detach().cpu().numpy(). output_hidden are your embeddings

    • @qaziacademy3048
      @qaziacademy3048 Год назад

      @@ЛидияШишина-у5ч yes

  • @anasssofti9271
    @anasssofti9271 Год назад +2

    It will help me a lot on my bioinformatics journey , thank you

  • @wolfpain5928
    @wolfpain5928 Год назад +2

    Thank you for this great job. Definitely I'm going to use this in my next streamlit app

  • @khanhnguyentan6613
    @khanhnguyentan6613 Год назад +2

    This is so interesting. Hope you can make a tutorial video on how to design new molecules based on deep learning. Thanks sir

  • @vasilispanagiotopoulos4681
    @vasilispanagiotopoulos4681 Год назад +2

    Hello sir, thanks for the very informative video. I tried to use your app placing a protein sequence from Uniprot (P34998 · CRFR1_HUMAN), but it showed no result... is there any restriction in the number of aminoacids used?? thank you

    • @DataProfessor
      @DataProfessor  Год назад

      Hi I think there's a limit of 400 amino acids

    • @wilcohermens3492
      @wilcohermens3492 Год назад

      @@DataProfessor adding ", max_chars=(400)" to the code for the textarea could be helpful then. Besides that, great application

  • @sapta9659
    @sapta9659 4 месяца назад

    Hi can you please make a video on fine tuning of Protein Large language models and getting sequence embeddings. Thank you for making all these videos, they are really helpful

  • @allensun3709
    @allensun3709 6 месяцев назад

    How do I get streamlit? There is an error when I type in the code into Jupyter, it does not recognize "streamlit"...

  • @nithyagobi-bn4fz
    @nithyagobi-bn4fz Год назад

    Could you please make video on protein mutation prediction server development like polyphen2, mutation assesser SNAP2

  • @yosufzamil
    @yosufzamil Год назад +1

    Thanks, sir. I watched your most of the videos. Helped a lot.
    I would like to know how we can interact with drugs and protein using ML,DL.

    • @DataProfessor
      @DataProfessor  Год назад +2

      Typically that could be done via molecular docking while can also be done via ML/DL so that'll require representing proteins and drugs as quantitative/qualitative (or also image/graph/etc) form that could subsequently be used as input for training.

    • @barryteffera1084
      @barryteffera1084 Год назад +1

      @@DataProfessorGreat video, I’d really appreciate a video where you demonstrate this as well

  • @ismaelsaidi-u7j
    @ismaelsaidi-u7j 8 месяцев назад

    do you know of a way to add constraint to the prediction. Let's say I did crosslink mass spec so I know some residue need to be close, can I add that to the prediction?

  • @Acer3859
    @Acer3859 Год назад +1

    This is awesome. Thanks for sharing it.

  • @danceprometheus
    @danceprometheus Год назад

    Really want to make a protein ligand docking app like AutoDock Vina. Would you do that next?

  • @eschoi
    @eschoi 8 месяцев назад

    Currently, the website is not working for query protein sequence.

  • @shoebkhan4076
    @shoebkhan4076 Год назад

    Your videos are great. Can you make a video on how to get started with snowpark(snowflakes python api)

  • @uminhtetoo
    @uminhtetoo Год назад +1

    Thank you for sharing, Sir.

  • @KENWASSERMAN
    @KENWASSERMAN Год назад

    Excellent! Please select a known drugable enzyme and add an analysis function to estimate the Kd for a candidate set of pharmacophores.

  • @fehmeedamustafa7049
    @fehmeedamustafa7049 Год назад

    Can we predict protein structure using graph data structures...any code available?

  • @Dr.Gashaw.M_Goshu
    @Dr.Gashaw.M_Goshu Год назад

    Thanks for sharing. Did you use random amino acid sequences or a known sequence?

  • @saipotmarkus123
    @saipotmarkus123 Год назад +2

    Very valuable content!

    • @DataProfessor
      @DataProfessor  Год назад +1

      Glad it was helpful!

    • @Quantumvp
      @Quantumvp Год назад +1

      @@DataProfessor Hi sir I am a chapter lead with Omdena and we are doing a project using the bioactivity data for breast cancer and I was wondering if you could be a guest speaker 🔊 in the a couple weeks.

    • @Quantumvp
      @Quantumvp Год назад +1

      @@DataProfessor it is based off of the course you conducted here on RUclips a year ago.

    • @DataProfessor
      @DataProfessor  Год назад

      @@Quantumvp Could you email me with further details

  • @rootnode
    @rootnode Год назад

    Nice one dude, thanks for this!

  • @fernandavictor5900
    @fernandavictor5900 Год назад

    Keep up the awesome work!!! I am suprised that you haven't researched "promo sm".