Currents in Bioinformatics

  • Dienstag 16:15 – 17:45 Uhr; SR 3423 EAP2
  • Beginn: 19.10.2021
  • Seminarleitung: Fleming Kretschmer

Vorläufiger Ablaufplan

Date Paper Presenter and Backup
19.10. Organisatorisches, Besprechen der Themen  
26.10. [6]  
2.11. [7]  
9.11.    
16.11.    
23.11.    
30.11.    
7.12.    
14.12.    
21.12.    
4.1. [1]  
11.1.    
18.1.    
25.1.    
1.2.    
8.2.    

List of papers:

alles vorläufig

([1]
B. Sanchez-Lengeling, E. Reif, A. Pearce, and A. B. Wiltschko, “A Gentle Introduction to Graph Neural Networks,” Distill, vol. 6, no. 9, p. e33, Sep. 2021, doi: 10.23915/distill.00033.)
[2]
A. D. Shrivastava, N. Swainston, S. Samanta, I. Roberts, M. W. Muelas, and D. B. Kell, “MassGenie: a transformer-based deep learning method for identifying small molecules from their mass spectra,” Bioinformatics, preprint, Jun. 2021. doi: 10.1101/2021.06.25.449969.
[3]
“Bi-modal Variational Autoencoders for Metabolite Identification Using Tandem Mass Spectrometry | bioRxiv.” https://www.biorxiv.org/content/10.1101/2021.08.03.454944v1 (accessed Oct. 19, 2021).
[4]
E. Litsa, V. Chenthamarakshan, P. Das, and L. Kavraki, “Spec2Mol: An end-to-end deep learning framework for translating MS/MS Spectra to de-novo molecules,” Sep. 2021, doi: 10.33774/chemrxiv-2021-6rdh6.
[5]
T. F. Leao et al., “A supervised fingerprint-based strategy to connect natural product mass spectrometry fragmentation data to their biosynthetic gene clusters,” Oct. 2021. doi: 10.1101/2021.10.05.463235.
[6]
J. Li and X. Jiang, “Mol-BERT: An Effective Molecular Representation with BERT for Molecular Property Prediction,” Wireless Communications and Mobile Computing, vol. 2021, pp. 1–7, Sep. 2021, doi: 10.1155/2021/7181815.
[7]
J. Jumper et al., “Highly accurate protein structure prediction with AlphaFold,” Nature, vol. 596, no. 7873, pp. 583–589, Aug. 2021, doi: 10.1038/s41586-021-03819-2.
 

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