NLM DIR Seminar Schedule
UPCOMING SEMINARS
RECENT SEMINARS
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Dec. 17, 2024 Joey Thole
Training set associations drive AlphaFold initial predictions of fold-switching proteins -
Dec. 10, 2024 Amr Elsawy
AI for Age-Related Macular Degeneration on Optical Coherence Tomography -
Dec. 3, 2024 Sarvesh Soni
Toward Relieving Clinician Burden by Automatically Generating Progress Notes -
Nov. 19, 2024 Benjamin Lee
Reiterative Translation in Stop-Free Circular RNAs -
Nov. 12, 2024 Devlina Chakravarty
Fold-switching reveals blind spots in AlphaFold predictions
Scheduled Seminars on June 2, 2022
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
The rapidly expanding catalog of microbial genomes and metagenomes has provided a wealth of information about what microbes are present in different environments and what functions are encoded in their genomes. Further analyses of these data can provide insights into the physiology of the organisms, their ecological significance, and potential clinical relevance. To facilitate the analysis of microbial genomes, we have developed a flexible and extensible annotation and search tool, ProkFunFind, that can be used to search for genes and gene clusters within collections of microbial genomes. ProkFunFind was designed to be flexible, incorporating multiple annotation tools, including eggNOG-mapper, KofamScan, and InterProScan, allowing users to perform searches based on sequence similarity, HMM profiles, or using established orthology definitions like NCBI’s COGs. Furthermore, we have designed our tool to be extensible, allowing for the future integration of additional annotation and search approaches. ProkFunFind has been successfully applied in multiple projects from our research group involving the characterization of metabolic pathways in the human gut microbiome, providing insights into their distribution and relevance to human health. One of these projects has been focused on characterizing the equol production gene cluster across available microbial genomes. The insights gained from our analysis of this gene cluster demonstrate the utility of this search approach and have expanded our knowledge of this biomedically important metabolic pathway. Our goal is to further refine and develop ProkFunFind, providing the microbial research community with an easy-to-use and flexible platform for the annotation of new functions.