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Molecular Artificial Intelligence & Digital Biochemistry
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Computational Structural Biology & Machine Learning for Biomolecules
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Molecular Machine Learning & Chemoinformatics for Drug Discovery
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Computational Structure-based Drug Discovery
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Molecular Modeling & Molecular Dynamics Simulation for Biomolecules
" SUCCESS DOES NOT COME FROM SMARTNESS
BUT IT'S CAUSED BY THE IMPLEMENTATION. "
MY ACHIEVEMENTS
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2024
Remarkable Ranking in the Top 20 (17th Place Out of 79 Participating Teams) for the Tox24 Challenge and The Solution has been Invited to be Published in Chemical Research in Toxicology (ChemResTox), ACS
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2024
Best Oral Presentation in Computational Biology Session, The 27th International Annual Symposium on Computational Science and Engineering (ANSCSE27)
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2023
JSTP Mentor for High School Student and Received Long-term Scholarship, National Science and Technology Development Agency (NSTDA)
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2023
Research Advisor for Genius Olympiad Finalists and Received Honorable Mention Award in Science, Genius Olympiad 2023
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2023
Research Advisor for ISEF Finalists and Received Fourth Place Award in Computational Biology and Bioinformatics, Regeneron ISEF 2023
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2023
Research Advisor for High School Students and Received Top Award and First Award of Thailand in Interdisciplinary Fields (Computational Biology & Bioinformatics), and Second Award of Thailand in Computer Science, Young Scientist Competition (YSC) 2023
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2022
Research Advisor for Genius Olympiad Finalists and Received Bronze Medal in Science, Genius Olympiad 2022
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2022
Research Advisor for ISEF Finalists and Received First Place Award in Computational Biology and Bioinformatics, Regeneron ISEF 2022
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2022
Research Advisor for High School Students and Received Top Award, First Award, and Second Award of Thailand in Interdisciplinary Fields (Computational Biology & Bioinformatics), Young Scientist Competition (YSC) 2022
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2021
Research Advisor for Genius Olympiad Finalists and Received Gold Medal in Science, Genius Olympiad 2021
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2021
Research Advisor for ISEF Finalists and Received First Place Award in Computational Biology and Bioinformatics, Regeneron ISEF 2021
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2021
Research Advisor for High School Students and Received Championship of Thailand in Computer Science, Young Scientist Competition (YSC) 2021
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2020
Research Advisor for High School Students and Received Championship of Thailand in Computer Science, Young Scientist Competition (YSC) 2020
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2018
Ph.D. scholarship from Vidyasirimedhi Institute of Science and Technology and PTT Group, and SCB
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2015
Academic Activist and Person who made reputation for Faculty of Science, Prince of Songkla University, Hatyai Campus, Thailand
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2015
Young Thai Science Ambassador 2014, National Science Museum, Thailand
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2014
The 11th True Young Webmaster Camp
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2013
Intermediate level (Band 4 of 6) in the PSU English Test
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2012
JSTP scholarship student, National Science and Technology Development Agency, Thailand
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2008 – 2010
Computer Olympiad Camp (POSN), 1st & 2nd camps, Walailak University, Thailand
EXPERIENCES
Recent Invited Talks
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Talk 99 – Poster Preparation for Science Project Presentation Workshop
EECi Young Innovator Contest 2024
Organized by Kamnoetvidya Science Academy (KVIS)
Venue: Kamnoetvidya Science Academy, Rayong
Date: Aug 24, 2024
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Talk 98 – Fun with Food
Fun Thinking with Science Around You Camp
for Grade 6 students of Anuban Ubonratchathani School, Ubon Ratchathani
Organized by National Science and Technology Development Agency (NSTDA)
Venue: Sirindhorn Science Home, Science Park, Pathum Thani
Date: Jul 11, 2024
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Talk 97 – Jump-start Science Project & Scientist Invents Dough
Jump Start Science Camp
for Grade 9 students of Horwang Pathumthani School, Pathum Thani
Organized by National Science and Technology Development Agency (NSTDA)
Venue: Sirindhorn Science Home, Thailand Science Park, Pathum Thani
Date: Jul 4–5, 2024
Outstanding Extracurricular Activities
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Regeneron International Science and Engineering Fair 2024 (Regeneron ISEF 2024)
Staff and Research Mentor
Fair: THA002 – Young Scientist Competition
Year: 2024 -
Regeneron International Science and Engineering Fair 2022 (Regeneron ISEF 2022)
Thai Interpreter
Year: 2022 -
Thailand Machine Learning for Chemistry Competition (TMLCC)
Organizer and Speaker
Lecture: Machine Learning for Molecular Chemistry in a Nutshell
Year: 2021 -
The White Room Enterprise Co., Ltd.
Co-founder
Science camps for students interested in science and education and charity camps for students underprivileged in science education
Year: 2012 – Present -
12th Young Webmaster Camp, Thailand Webmaster Association
Organizer
Year: 2015
Research Experience
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Artificial Intelligence-driven Prediction of Molecular Properties and Bioactivity for Cancer Therapeutics Using Graph Neural Networks
Mentors: Assoc. Prof. Dr. Sarana Nutanong, and Assoc. Prof. Dr. Thanyada Rungrotmongkol
Year: 2018 – Now -
Computational Screening of Tripeptides Against Kinase-Domain for Human Epidermal Growth Factor Receptor 2 (HER2)
Research Experience at NSTDA, Thailand (JSTP Scholarship)
Mentors: Assoc. Prof. Dr. Kiattawee Choowongkomon, Dr. Sissades Tongsima
Year: 2014 – 2017 -
Characterization of Gelatin From Silver Carp Skin As Influenced by Acid Pretreatment
Research Experience at Fac. Agro-Industry, PSU, Thailand (JSTP Scholarship)
Mentor: Prof. Dr. Soottawat Benjakul
Year: 2011 – 2012
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RESEARCH INTERESTS
The research focuses on exploring new frontiers in Molecular Property & Interaction, Molecular Design & Discovery, and Molecular Representation & Learning, aiming to revolutionize the understanding and application that contribute significant strides for (bio)molecular science by integrating cutting-edge computational techniques and interdisciplinary knowledge from Biochemistry, Chemistry, Pharmaceutical Sciences, and Computer Science.
The current research themes, collectively termed “CompMol3D – Computational Molecular Discovery, Design, and Development”, encompass the following areas:
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Molecular Property & Interaction
Elucidate relationships between (bio)molecular structures, properties, and interactions, informing predictions and facilitating new discoveries.
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Molecular Design & Discovery
Utilize structural analysis to innovate in the discovery, design, and understanding of (bio)molecular phenomena, creating new pathways for molecular development and applications.
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Molecular Representation & Learning
Develop advanced model architectures and feature engineering strategies, enhancing machine learning and deep learning model performance in (bio)molecular science.
- Computational Chemistry
- Computational Biology
- Structural Bioinformatics
- Drug Discovery
- Machine Learning
- Deep Learning
Current Research Projects
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Molecular Representation Learning for Drug Design & Discovery
This project focuses on developing advanced molecular representation learning techniques, utilizing deep learning models (i.e. graph neural networks) to enhance cancer drug discovery processes. The goal is to improve the prediction of molecular properties and interactions, contributing to more efficient drug design and development.
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Multimodal Deep Learning Based-on Multi-Omics for Drug Response Prediction and Biomarker Discovery
This project focuses on developing multimodal deep learning models integrated with multi-omics data (i.e. genomics, transcriptomics, and proteomics), aiming to predict cancer drug responses and discover novel cancer biomarkers. This approach leverages the power of machine learning to uncover complex relationships between various biological data types, enhancing personalized medicine strategies.
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Machine Learning and Computational Biology for Drug Design & Discovery, Enzyme Engineering, and Structural Biology
This project integrates machine learning and computational biology to address challenges in drug discovery, enzyme engineering, and structural biology. By leveraging advanced techniques, the project aims to predict and design novel molecules for cancer protein targets, optimize enzymes for applications such as PET degradation, and explore the structural biology of proteins, including Asgard archaea and chitin degradation proteins. This holistic approach enhances the understanding of complex biological systems and promotes the development of innovative biotechnological solutions.
Future Research Projects
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Machine Learning and Computational Biology for Peptide- and Nucleotide-Based Therapeutics
This project will focus on leveraging machine learning and computational biology to design and optimize peptide- and nucleotide-based therapeutics, including cyclic peptides, etc. These therapeutic modalities are gaining traction in treating various diseases, and advanced computational methods will accelerate their discovery and development.
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Deep Learning for Epitranscriptomics
This project aims to develop deep learning models to explore the emerging field of epitranscriptomics, which studies chemical modifications on RNA molecules. This approach will facilitate the identification of these modifications and their role in disease mechanisms, opening new avenues for therapeutic interventions.
- Graph Neural Networks
- Molecular Representation Learning
- Unsupervised Pretraining
- Cancer Driver Gene
- Cancer Biomarker
- Cancer Drug Response
- Cancer Drug Combinations
- Personalized Medicine
- Multi-omics
- Molecular Docking
- Molecular Dynamics Simulation
- Epitranscriptomics
- Peptide-Based Therapeutics
- Nucleotide-Based Therapeutics
Research Publications
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Boonyarit, B., Yamprasert, N. , Kaewnuratchadasorn, P., Kinchakawat, J., Prommin, C., Rungrotmongkol, T., & Nutanong, S., (2024). GraphEGFR: Multi-task and Transfer Learning Based on Molecular Graph Attention Mechanism and Fingerprints Improving Inhibitor Bioactivity Prediction for EGFR Family Proteins on Data Scarcity. Journal of Computational Chemistry, 45(23), 2001-2023.
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Virakarin, P., Saengnil, N., Boonyarit, B., Kinchagawat, J., Laotaew, R., Saeteng, T., Nilsu, T., Suvannang, N., Rungrotmongkol, T. & Nutanong, S. (2020). LigEGFR: Spatial graph embedding and molecular descriptors assisted bioactivity prediction of ligand molecules for epidermal growth factor receptor on a cell line-based dataset. bioRxiv.
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Boonyarit B, Mokmak W, Tongsima S, & Choowongkomon K. (2016). Computational screening of tripeptides against kinase-domain for human epidermal growth factor receptor 2 (HER2). The 42nd Congress on Science and Technology of Thailand (STT42), 495-504.
Research Collaborations
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Prof. Robert (Bob) Charles Robinson
- School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology, Wang Chan, Rayong, Thailand
- Research Institute of Interdisciplinary Science, Okayama University, Japan -
Prof. Dr. Wipa Suginta
School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology, Wang Chan, Rayong, Thailand
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Assoc. Prof. Dr. Thanyada Rungrotmongkol
Department of Biochemistry, Faculty of Science, Chulalongkorn University, Pathum Wan, Bangkok, Thailand
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Dr. Chayanon Ngambenjawong
School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology, Wang Chan, Rayong, Thailand
RESEARCH ADVISEMENT
Students: 1. Phongsakorn Sriwicha
Advisors: Bundit Boonyarit
School: Sakolraj Wittayanukul School
Year: 2024 – 2024
Students: 1. Panuwat Wongpattanawut, 2. Phurivet Methmaolee
Advisors: Theerawut Chantapan and Bundit Boonyarit
School: Princess Chulabhorn Science High School Mukdahan
Year: 2022 – 2023
Students: 1. Tisorn Na phattalung, 2. Matin Kositchutima, 3. Kittiphat Pongarunotai
Advisors: Dr. Thanasan Nilsu and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2022 – 2023
Students: 1. Tisorn Na phattalung, 2. Surapa Panjaphakdee, 3. Matin Kositchutima
Advisors: Dr. Thanasan Nilsu and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2021 – 2022
Students: 1. Pawit Kaewnuratchadasorn, 2. Wutthipong Chongchareansanti, 3. Nattawin Yamprasert
Advisors: Dr. Sarote Boonseng and Bundit Boonyarit
School: Mahidol Wittayanusorn School (MWIT)
Year: 2021 – 2022
Students: 1. Thiranich Sawatdipap, 2. Phanfa Laohasinnuruk
Advisors: Dr. Tanawan Leeboonngam and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2021 – 2022
Students: 1. Theeradon Sakpetch, 2. Phandej Soisamuth
Advisors: Dr. Thanasan Nilsu and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2021 – 2022
Students: 1. Parajaree Ungudonpakdee, 2. Thanasan Kumdee
Advisors: Dr. Thanasan Nilsu and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2020 – 2021
Students: 1. Theeradon Sakpetch, 2. Phandej Soisamuth
Advisors: Dr. Thanasan Nilsu and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2020 – 2021
Students: 1. Natthakan Saeng-nil, 2. Puri Virakarin
Advisors: Dr. Thanasan Nilsu and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2020 – 2021
Students: 1. Natthakan Saeng-nil, 2. Puri Virakarin
Advisors: Dr. Thanasan Nilsu and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2019 – 2020
Students: 1. Chawapon Tritipchatsakun, 2. Thanis Prucksikanont
Advisors: Pimsiri Danphitsanuparn and Bundit Boonyarit
School: Kamnoetvidya Science Academy (KVIS)
Year: 2018 – 2019
- Graph Convolutional Network (GCN)
- Graph Attention Network (GAT)
- Spatial Graph Embedding Network
- Transfer Learning
- Multi-task Learning
- Semi-Supervised Learning
- Unsupervised Pretraining
BioXcepTion is a high school student research team with a particular emphasis on Computational Biology, Computational Chemistry, and Artificial Intelligence.
(Click arrow for more information about our student research team)
PERSONAL
I also have other interests including graphics design, presentation design, web design, online learning design, and server administration.
Graphics & Presentation Design
I have been interested in graphics and presentation design since I was an undergraduate student. I am most good a PR media design such as posters, brochures, and book covers. I have also been invited to lecture on the design for research presentation to school students and researchers.
Online Learning Design
I got an excellent chance from the Department of Chemistry, Faculty of Science Chulalongkorn University to build online learning for Stereochemistry Lecture Series. This lesson is used in organic chemistry classes for undergraduate students. The instructional material includes videos and interactive activities.
Server Administration
I also have been interested in server administration for computational science research. In basic, I have used CentOS operating system and Slurm job scheduler for operation and management. For more detail, you can visit my GitHub for the setup instruction.
CONTACT
Bundit Boonyarit
Email: [email protected]
Email: [email protected]