| _version_ | 1866902258910756864 |
|---|---|
| author | Guo, Tiannan |
| author_facet | Guo, Tiannan |
| contents | <p>Description (abstract)<br>In this talk, I will share our latest thoughts and results on AI-empowered proteomics, highlighting several ongoing projects. Firstly, we developed a large-scale pretrained transformer model for analyzing DIA data, implemented in a tool called DIA-BERT. Secondly, I will introduce another large AI model, DDA-BERT for analyzing DDA data. Lastly, I will discuss an international AI proteomics initiative and invite collaboration and comments to the MassNet project.</p> <p>Speaker bio<br>Tiannan Guo received training of clinical medicine (1999-2006) at Tongji Medical College, Huazhong University of Science and Technology, and learned biology (2001-2005) at Wuhan University before he moved to Singapore for PhD training in cancer proteomics (2008-2012) in the laboratories of Dr. Newman Sze in Nanyang Technological University and Dr. Oi Lian Kon in National Cancer Centre Singapore. In 2012, Tiannan started his postdoctoral training in the laboratory of Dr. Ruedi Aebersold in ETH Zurich. Tiannan moved to Sydney as the Scientific Director of ProCan, group leader of Cancer Proteome, Children's Medical Research Institute, and the conjoint senior lecturer at The University of Sydney Medical School, in March 2017.</p> <p>Tiannan joined the Westlake Institute for Advanced Studies, Westlake University in August 2017 as an Assistant Professor with tenure track, and was promoted to tenured Associate Professor in Jan 2023. He is the Director of iMarker lab (upgraded to Westlake Center for Intelligent Proteomics) at Westlake Laboratory in 2020, and an Associate Faculty Member of the Research Center for Industries of the Future at Westlake University. He also serves in multiple journals, including Molecular & Cellular Proteomics, Proteomics, Proteomics Clinical Applications, Clinical Proteomics, Genomics Proteomics Bioinformatics, Cell Reports Medicine, and Scientific Data. In 2023 and 2024, he was consecutively selected for the “Top 2% Scientists Worldwide” list published by Stanford University.</p> <p>We aim to develop mass spectrometry-based protein technologies to decipher the proteome complexity, with a focus on understudied proteins, and facilitate disease diagnosis, treatment and drug discovery.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18476541 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | From Proteomic Big Data to AI Proteomics Guo, Tiannan proteomics DIA AI transformer DIA-BERT DDA-BERT OES2024 <p>Description (abstract)<br>In this talk, I will share our latest thoughts and results on AI-empowered proteomics, highlighting several ongoing projects. Firstly, we developed a large-scale pretrained transformer model for analyzing DIA data, implemented in a tool called DIA-BERT. Secondly, I will introduce another large AI model, DDA-BERT for analyzing DDA data. Lastly, I will discuss an international AI proteomics initiative and invite collaboration and comments to the MassNet project.</p> <p>Speaker bio<br>Tiannan Guo received training of clinical medicine (1999-2006) at Tongji Medical College, Huazhong University of Science and Technology, and learned biology (2001-2005) at Wuhan University before he moved to Singapore for PhD training in cancer proteomics (2008-2012) in the laboratories of Dr. Newman Sze in Nanyang Technological University and Dr. Oi Lian Kon in National Cancer Centre Singapore. In 2012, Tiannan started his postdoctoral training in the laboratory of Dr. Ruedi Aebersold in ETH Zurich. Tiannan moved to Sydney as the Scientific Director of ProCan, group leader of Cancer Proteome, Children's Medical Research Institute, and the conjoint senior lecturer at The University of Sydney Medical School, in March 2017.</p> <p>Tiannan joined the Westlake Institute for Advanced Studies, Westlake University in August 2017 as an Assistant Professor with tenure track, and was promoted to tenured Associate Professor in Jan 2023. He is the Director of iMarker lab (upgraded to Westlake Center for Intelligent Proteomics) at Westlake Laboratory in 2020, and an Associate Faculty Member of the Research Center for Industries of the Future at Westlake University. He also serves in multiple journals, including Molecular & Cellular Proteomics, Proteomics, Proteomics Clinical Applications, Clinical Proteomics, Genomics Proteomics Bioinformatics, Cell Reports Medicine, and Scientific Data. In 2023 and 2024, he was consecutively selected for the “Top 2% Scientists Worldwide” list published by Stanford University.</p> <p>We aim to develop mass spectrometry-based protein technologies to decipher the proteome complexity, with a focus on understudied proteins, and facilitate disease diagnosis, treatment and drug discovery.</p> |
| title | From Proteomic Big Data to AI Proteomics |
| topic | proteomics DIA AI transformer DIA-BERT DDA-BERT OES2024 |
| url | https://doi.org/10.5281/zenodo.18476541 |