Yuzhen Ye and Haixu Tang, professors of informatics and computer science at the School of Informatics, Computing, and Engineering, have been awarded $1.1 million from the National Institute of Health to develop and expand computational approaches to derive bacterial marker genes and pathways from microbiome data.
Microbes are all around us, and they play a critical role in sustaining life. Effective detection of microbial biomarkers associated with diseases, such as type II diabetes, liver cancer, and inflammatory bowel disease, can lead to earlier detection and better treatment.
“We’re thrilled to receive this grant from the NIH to continue our work on microbiome data,” Ye said. “It’s an exciting extension of what I’ve been working on, which is development of new algorithms and tools using a subtractive assembly approach for making sense of the wealth of microbiome data that is being generated.”
Subtractive assembly approaches to microbiome sequencing data analysis can identify microbial genes and pathways associated with diseases. The approach relies on differential biomarkers -- such as species, genes and biological pathways -- to differentiate between different groups of microbiomes. The project aims to improve and extend these approaches.
“We hope to apply our methods to the abundant metagenomic data acquired from human patients’ microbiome, hopefully to identify markers that can be clinical use,” said Tang, who also is the director of data science academic programs at the School of Informatics, Computing and Engineering.
Ultimately, the tools will be useful for translational applications of microbiome data for disease diagnosis, treatment responsiveness prediction, and disease prevention.
“This work will advance the science in Precision Health, a major initiative within IU,” said Kay Connelly, the associate dean for research at SICE. “Understanding the microbiome and how it impacts our health is incredibly important for tailoring individual treatment plans to patients. Professors Ye and Tang are at the forefront of this field.”
The NIH grant, “Subtractive assembly approaches for inferring disease-associated microbial genes and pathways from microbiome sequencing data,” will extend through 2022.