Metagenomics studies have provided key insights into the composition and structure of microbial communities found in different environments. Among the techniques used to analyze metagenomic data, binning is considered as a crucial step in order to characterize the different species of microorganisms present in microbial communities. We propose two binning methods, GraphBin and MetaBCC-LR, to bin metagenomic sequences. GraphBin makes use of the assembly graph to refine binning results and to enable detecting shared sequences among multiple species. MetaBCC-LR is a reference-free binning method which directly clusters long reads based on their k-mer coverage histograms and oligonucleotide composition.
Senior Lecturer, The School of Computing, Australian National University
Yu Lin is a Senior Lecturer and leads the Computational Genomics Group at the School of Computing, Australian National University. Prior to this, he was a postdoctoral fellow at the Department of Computer Science and Engineering, University of California San Diego (UCSD). He received his PhD in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. His research focuses on computational biology and bioinformatics, and he has been working on models and algorithms for genome assembly, metagenomics and comparative genomics. In 2020, he received the Outstanding Contribution by an Early Career Researcher Award from the Australian Bioinformatics and Computational Biology Society.