esp_s2025

Emerging Scholars Program with Christopher Chow

https://github.com/chiush/esp_s2025

Science Score: 31.0%

This score indicates how likely this project is to be science-related based on various indicators:

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Low similarity (3.4%) to scientific vocabulary

Last synced: 10 months ago · JSON representation ·

Repository

Emerging Scholars Program with Christopher Chow

Basic Info

Host: GitHub
Owner: ChiuSH
Language: Python
Default Branch: main
Size: 28.8 MB

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Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 0

Created over 1 year ago · Last pushed about 1 year ago

Metadata Files

Readme Citation

README.md

The plan for Emerging Scholars Program Spring 2025:

Week 1 (2/27-3/5)

   1. find/upload some papers of PTMs with machine learning

   2. decide the direction of this project

   3. search the avaiable database for PTMs

   4. next meeting 3/6

week 2 (3/6-3/13)

   1. foucs on CNN model 

   2. try to find databases, papers of CNN learning on PTMs

   3. next meeting 3/13

Week 3-4 (3/14-3/26)

   1. build a CNN model for PTMs

   2. train the model and see the results

   3. consider a CNN model with attention head(s)

   4. next meeting 3/20

week 5-6 (3/27-4/9)

   1. post-processing the results

   2. figure out the way to do poster presenting

week 7-8 (4/10-4/24)

   1. start to edit the poster

   2. think how to do the story telling

   3. prepare for presentation

week 9 (4/25-4/30)

   1. print out the poster

   2. prepare for presentation

Owner

Login: ChiuSH
Kind: user

Repositories: 1
Profile: https://github.com/ChiuSH

Citation (citations for abstract.txt)

Zhong Q, Xiao X, Qiu Y, Xu Z, Chen C, Chong B, Zhao X, Hai S, Li S, An Z, Dai L. Protein posttranslational modifications in health and diseases: Functions, regulatory mechanisms, and therapeutic implications. MedComm (2020). 2023 May 2;4(3):e261. doi: 10.1002/mco2.261. PMID: 37143582; PMCID: PMC10152985.

Yu-Xiang Huang, Rong Liu, Improved prediction of post-translational modification crosstalk within proteins using DeepPCT, Bioinformatics, Volume 40, Issue 12, December 2024, btae675, https://doi.org/10.1093/bioinformatics/btae675

Keenan EK, Zachman DK, Hirschey MD. Discovering the landscape of protein modifications. Mol Cell. 2021 May 6;81(9):1868-1878. doi: 10.1016/j.molcel.2021.03.015. Epub 2021 Apr 1. PMID: 33798408; PMCID: PMC8106652.

Meng L, Chan WS, Huang L, Liu L, Chen X, Zhang W, Wang F, Cheng K, Sun H, Wong KC. Mini-review: Recent advances in post-translational modification site prediction based on deep learning. Comput Struct Biotechnol J. 2022 Jun 30;20:3522-3532. doi: 10.1016/j.csbj.2022.06.045. PMID: 35860402; PMCID: PMC9284371.

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