New preprint: "Integrative chromatin state annotation of 234 human ENCODE4 cell types using Segway reveals disease drivers" @marjanfarahbod @mforoozz @HDaneshpajouh @bonscotthoughts @JMichaelCherry1 @maxlibbrecht biorxiv.org/content/10.1101/…

New paper in @OUPBioinfo: "Integrative chromatin domain annotation through graph embedding of Hi-C data", Neda Shokraneh, Mariam Arab, @maxlibbrecht.

3\ The paper is available here: pubmed.ncbi.nlm.nih.gov/3416…

2\ bacterial pathogen within a single human host has important implications for public health. In this research, we introduce SplitStrains, a novel method grounded in a rigorous statistical model, estimates mixed strains' proportions and deconvolves them.

1\ Einar Gabbassov, Miguel Moreno-Molina, Iñaki Comas, Maxwell Libbrecht, and Leonid Chindelevitch published their work on "SplitStrains, a tool to identify and separate mixed Mycobacterium tuberculosis infections from WGS data". Since the occurrence of multiple strains of a

Mohammad Sadegh Saberian defended his MSc thesis on Using DNNs in multiple instance learning to identify putative treatments effective against SARS-CoV-2 based on morphological analysis. Congratulations, Mohammad Sadegh!

1\ Kevin Dsouza, and Adam Li submitted a paper on " Latent representation of the human pan-celltype epigenome through a deep recurrent neural network". In this research, we propose Epi-LSTM, a deep long short-term memory (LSTM) recurrent neural network autoencoder to capture the

@maxlibbrecht, @rachelcwchan and @michaelhoffman just submitted a review of segmentation and genome annotation (SAGA) algorithms such as Segway and ChromHMM. Check out the preprint here: arxiv.org/abs/2101.00688