Using AI/ML to transform molecular biology databases
Конференцијски прилог (Објављена верзија)
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© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
Метаподаци
Приказ свих података о документуАпстракт
We are living through a revolution in AI approaches, which is transforming molecular
biology and computational biology. I will discuss how the advent of high accuracy structural
models has made a large impact in our ability to completely and accurately classify protein
domains. I will also talk about how Deep Learning models such as ProtENN developed by
Google Research have expanded our ability to find distant homologues for known protein
families. I will argue that these models represent the most significant change in protein
classification in three decades. Even more recently we have seen to arrival of Large
Language Models such as ChatGPT, which may now enable us to develop high throughput
tools for annotating proteins, non-coding RNAs and families, if only we can stop them
hallucinating! I will talk about our efforts to harness these models to write accurate and
verifiable annotation at scale.
Кључне речи:
AI / protein domains / molecular biology databasesИзвор:
4th Belgrade Bioinformatics Conference, 2023, 4, 9-9Издавач:
- Belgrade : Institute of molecular genetics and genetic engineering
Напомена:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Колекције
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Bateman, Alex PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/1944 AB - We are living through a revolution in AI approaches, which is transforming molecular biology and computational biology. I will discuss how the advent of high accuracy structural models has made a large impact in our ability to completely and accurately classify protein domains. I will also talk about how Deep Learning models such as ProtENN developed by Google Research have expanded our ability to find distant homologues for known protein families. I will argue that these models represent the most significant change in protein classification in three decades. Even more recently we have seen to arrival of Large Language Models such as ChatGPT, which may now enable us to develop high throughput tools for annotating proteins, non-coding RNAs and families, if only we can stop them hallucinating! I will talk about our efforts to harness these models to write accurate and verifiable annotation at scale. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - Using AI/ML to transform molecular biology databases EP - 9 SP - 9 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_1944 ER -
@conference{ author = "Bateman, Alex", year = "2023", abstract = "We are living through a revolution in AI approaches, which is transforming molecular biology and computational biology. I will discuss how the advent of high accuracy structural models has made a large impact in our ability to completely and accurately classify protein domains. I will also talk about how Deep Learning models such as ProtENN developed by Google Research have expanded our ability to find distant homologues for known protein families. I will argue that these models represent the most significant change in protein classification in three decades. Even more recently we have seen to arrival of Large Language Models such as ChatGPT, which may now enable us to develop high throughput tools for annotating proteins, non-coding RNAs and families, if only we can stop them hallucinating! I will talk about our efforts to harness these models to write accurate and verifiable annotation at scale.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "Using AI/ML to transform molecular biology databases", pages = "9-9", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_1944" }
Bateman, A.. (2023). Using AI/ML to transform molecular biology databases. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 9-9. https://hdl.handle.net/21.15107/rcub_imagine_1944
Bateman A. Using AI/ML to transform molecular biology databases. in 4th Belgrade Bioinformatics Conference. 2023;4:9-9. https://hdl.handle.net/21.15107/rcub_imagine_1944 .
Bateman, Alex, "Using AI/ML to transform molecular biology databases" in 4th Belgrade Bioinformatics Conference, 4 (2023):9-9, https://hdl.handle.net/21.15107/rcub_imagine_1944 .