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Paper Abstract and Keywords
Presentation 2024-03-13 15:25
Machine learning-based solubility prediction and meta-heuristic search for multiple mutation patterns
Kaisei Kojima, Kazutoshi Sakakibara, Masaki Nakamura (Toyama Prefectural Univ.), Daisuke Matsui (Ritsumeikan Univ.) MSS2023-80 NLP2023-132
Abstract (in Japanese) (See Japanese page) 
(in English) In order to solubilize insoluble proteins that cannot be used for industrial purposes, experiments have been performed to mutate a part of the protein to make it soluble. However, the number of possible mutation combinations is large, and we investigate an efficient method to find mutation patterns that improve solubility by using machine learning models to predict solubility based on amino acid sequence information, and by searching multiple mutations using meta-heuristics.
Keyword (in Japanese) (See Japanese page) 
(in English) protein / solubility / machine learning / meta-heuristics / simulated annealing / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 427, MSS2023-80, pp. 48-53, March 2024.
Paper # MSS2023-80 
Date of Issue 2024-03-06 (MSS, NLP) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF MSS2023-80 NLP2023-132

Conference Information
Committee NLP MSS  
Conference Date 2024-03-13 - 2024-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Kikai-Shinko-Kaikan Bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) MSS, NLP, etc. 
Paper Information
Registration To MSS 
Conference Code 2024-03-NLP-MSS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Machine learning-based solubility prediction and meta-heuristic search for multiple mutation patterns 
Sub Title (in English)  
Keyword(1) protein  
Keyword(2) solubility  
Keyword(3) machine learning  
Keyword(4) meta-heuristics  
Keyword(5) simulated annealing  
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1st Author's Name Kaisei Kojima  
1st Author's Affiliation Toyama Prefectural University (Toyama Prefectural Univ.)
2nd Author's Name Kazutoshi Sakakibara  
2nd Author's Affiliation Toyama Prefectural University (Toyama Prefectural Univ.)
3rd Author's Name Masaki Nakamura  
3rd Author's Affiliation Toyama Prefectural University (Toyama Prefectural Univ.)
4th Author's Name Daisuke Matsui  
4th Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
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Speaker Author-1 
Date Time 2024-03-13 15:25:00 
Presentation Time 25 minutes 
Registration for MSS 
Paper # MSS2023-80, NLP2023-132 
Volume (vol) vol.123 
Number (no) no.427(MSS), no.428(NLP) 
Page pp.48-53 
#Pages 6 
Date of Issue 2024-03-06 (MSS, NLP) 

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