I'm afraid that I don't understand this diagram indicating that proteins go throuh metabolism and end up with biochemicals like carbohydrates. There are some mechanisms that carbohydrates can be switched into amino acids and vice versa,  but there are also amino acids that human body can not produce. Plus how lipids can be made out of proteins...?(00:03:37 - 00:10:57) - Multiomics Data for Cancer Diagnosis (AlphaCare: Episode 3)

I'm afraid that I don't understand this diagram indicating that proteins go throuh metabolism and end up with biochemicals like carbohydrates. There are some mechanisms that carbohydrates can be switched into amino acids and vice versa, but there are also amino acids that human body can not produce. Plus how lipids can be made out of proteins...?(00:03:37 - 00:10:57)
Multiomics Data for Cancer Diagnosis (AlphaCare: Episode 3)

The amount of molecular biology datasets available are growing exponentially every month. Multiomics consist of all the layers of the molecular biome; the genome, epigenome, transcriptome, proteome, and metabolome. In this episode, we're going to learn how each of the layers of the molecular biol...
The amount of molecular biology datasets available are growing exponentially every month. Multiomics consist of all the layers of the molecular biome; the genome, epigenome, transcriptome, proteome, and metabolome. In this episode, we're going to learn how each of the layers of the molecular biology stack work, and then look at 3 different real world use cases for Cancer patients (diagnostic, prognostic, and predictive) using open-source python code on GitHub. Then we'll look at how a Generative Adversarial Network can be used to generate synthetic genomic data to battle imbalanced classes. Enjoy!

Big thanks to RapidAPI for sponsoring this video series:
https://rapidapi.com/hub?utm_source=Siraj-Raval&utm_medium=DevRel&utm_campaign=DevRel

Omics Datasets:
https://www.omicsdi.org/search

More Omics Datasets:
https://www.ncbi.nlm.nih.gov/geo/browse/?view=series&display=20&zsort=samples

Code Credits:
Example 1 (CITE-Seq autoencoder prognosis):
https://github.com/naity/citeseq_autoencoder

Example 2 (UMAP diagnosis):
https://github.com/NikolayOskolkov/UMAPDataIntegration

Example 3 (AlphaFold Protein Folding Prediction:
https://alphafold.ebi.ac.uk/
https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb#scrollTo=KK7X9T44pWb7

Example 4 (GAN for Genomic Data Synthesis):
https://github.com/Unique-Divine/GANs-for-Genomics

Generative Biome HTML:
https://github.com/marpi/biomes

More Learning Resources:

AlphaCare Episode 1:
https://www.youtube.com/watch?v=fGv6VmfGMLc

AlphaCare Episode 2:
https://www.youtube.com/watch?v=PrqdEJZOrWE&t=10s

AlphaFold Tutorial:
https://www.youtube.com/watch?v=GQH-zWUylPY

How I Gamify Learning:
https://www.youtube.com/watch?v=nH85q7gC8uw

Learn Machine Learning in 3 months:
https://www.youtube.com/watch?v=Cr6VqTRO1v0

Multiomics Paper 1:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003173/

Multiomics Paper 2:
https://www.frontiersin.org/articles/10.3389/fgene.2020.610798/full

Follow me:

INSTAGRAM:
https://www.instagram.com/sirajraval/

TWITTER:


FACEBOOK:
https://www.facebook.com/sirajologyyy

LINKEDIN:
https://www.linkedin.com/in/sirajraval/

Please subscribe for more programming videos! That's what keeps me going. Join my AI community: http://chatgptschool.io/ Sign up for my AI Sports betting Bot, WagerGPT! (500 spots available):
https://www.wagergpt.co

#siraj #siraj raval #machine learning #deep learning #healthcare #health tech #generative adversarial networks #GANs #multiomics #python #programming #tutorial

Siraj Raval

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Timetable

動画タイムテーブル

動画数:471件

. - I Built a Sports Betting Bot (WagerGPT)

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I Built a Sports Betting Bot (WagerGPT)
2024年01月04日  @ckq 様 
00:02:22 - 00:05:48
that’s an outdated player roster from 3 years ago buddy - I Built a Sports Betting Bot (WagerGPT)

that’s an outdated player roster from 3 years ago buddy

I Built a Sports Betting Bot (WagerGPT)
2024年01月04日  @metalflames4 様 
00:02:22 - 00:05:48
fwiw they went 1-3 on those picks - I Built a Sports Betting Bot (WagerGPT)

fwiw they went 1-3 on those picks

I Built a Sports Betting Bot (WagerGPT)
2024年01月04日  @ckq 様 
00:02:40 - 00:05:48
😂 - I Built a Sports Betting Bot (WagerGPT)

😂

I Built a Sports Betting Bot (WagerGPT)
2024年01月04日  @tennisprotrader 様 
00:05:22 - 00:05:48
the lie. any apple m* processor has it, even many phone processor have - Deep Learning with 4th Gen Xeon Processors and Intel® Accelerator Engines (AWS re:Invent 2023)

the lie. any apple m* processor has it, even many phone processor have

Deep Learning with 4th Gen Xeon Processors and Intel® Accelerator Engines (AWS re:Invent 2023)
2023年12月14日  @somerndid 様 
00:02:01 - 00:04:50
@ you are showing what appears to be yet another medical dataset "medalpaca/medical_meadow_mediqa" but it is unclear how that is used. - DoctorGPT: Offline & Passes Medical Exams!

@ you are showing what appears to be yet another medical dataset "medalpaca/medical_meadow_mediqa" but it is unclear how that is used.

DoctorGPT: Offline & Passes Medical Exams!
2023年08月13日  Mark Woodworth 様 
00:13:12 - 00:18:13
@What exactly are you concatenating? You say "instruction column and input column into a single input" but the code references only the "question" column from the "GBaker/MedQA-USMLE-4-options" dataset.  The question is then submitted for inference as-is, without being combined with anything as far as I can tell. Also - are the options (answer choices) and correct_answer_idx (multiple choice answer) used anywhere? - DoctorGPT: Offline & Passes Medical Exams!

@What exactly are you concatenating? You say "instruction column and input column into a single input" but the code references only the "question" column from the "GBaker/MedQA-USMLE-4-options" dataset. The question is then submitted for inference as-is, without being combined with anything as far as I can tell. Also - are the options (answer choices) and correct_answer_idx (multiple choice answer) used anywhere?

DoctorGPT: Offline & Passes Medical Exams!
2023年08月13日  Mark Woodworth 様 
00:13:21 - 00:13:12
@ you mention SFT with the base model, but the code appears to be using the chat model - DoctorGPT: Offline & Passes Medical Exams!

@ you mention SFT with the base model, but the code appears to be using the chat model

DoctorGPT: Offline & Passes Medical Exams!
2023年08月13日  Mark Woodworth 様 
00:18:13 - 00:38:49