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Revisiting microbe-metabolite interactions: doing better than random
(2019)bioRxivRecently, Quinn and Erb et al [1] made the case that when used correctly, correlation and proportionality can outperform MMvec when identifying microbe-metabolite interactions. We revisit this comparison and show that the proposed correlation and proportionality are outperformed by MMvec on real data due to their inability to deal with sparsity commonly observed in microbiome and metabolome datasets.Working Paper -
Structure and function of a neocortical synapse
(2019)bioRxivThirty-four years since the small nervous system of the nematode C. elegans was manually reconstructed in the electron microscope (EM)1, ‘high-throughput’ EM techniques now enable the dense reconstruction of neural circuits within increasingly large brain volumes at synaptic resolution2–6. As with C. elegans, however, a key limitation for inferring brain function from neuronal wiring diagrams is that it remains unknown how the structure ...Working Paper -
Structured hierarchical models for probabilistic inference from perturbation screening data
(2019)bioRxivGenetic perturbation screening is an experimental method in biology to study cause and effect relationships between different biological entities. However, knocking out or knocking down genes is a highly error-prone process that complicates estimation of the effect sizes of the interventions. Here, we introduce a family of generative models, called the structured hierarchical model (SHM), for probabilistic inference of causal effects from ...Working Paper -
Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens
(2019)bioRxivDespite the progress in precision oncology, development of cancer therapies is limited by the dearth of suitable drug targets1. Novel candidate drug targets can be identified based on the concept of synthetic lethality (SL), which refers to pairs of genes for which an aberration in either gene alone is non-lethal, but co-occurrence of the aberrations is lethal to the cell. We developed SLIdR (Synthetic Lethal Identification in R), a ...Working Paper -
Co-catabolism of arginine and succinate drives symbiotic nitrogen fixation
(2019)bioRxivBiological nitrogen fixation emerging from the symbiosis between bacteria and crop plants holds a significant promise to increase the sustainability of agriculture. One of the biggest hurdles for the engineering of nitrogen-fixing organisms is to identify the metabolic blueprint for symbiotic nitrogen fixation. Here, we report on the CATCH-N cycle, a novel metabolic network based on co-catabolism of plant-provided arginine and succinate ...Working Paper -
The type IV pilin PilA couples surface attachment and cell cycle initiation in Caulobacter crescentus
(2019)bioRxivUnderstanding how bacteria colonize surfaces and regulate cell cycle progression in response to cellular adhesion is of fundamental importance. Here, we used transposon sequencing in conjunction with FRET microscopy to uncover the molecular mechanism how surface sensing drives cell cycle initiation in Caulobacter crescentus. We identified the type IV pilin protein PilA as the primary signaling input that couples surface contact to cell ...Working Paper -
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immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking
(2019)bioRxivB- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor ...Working Paper -
Deep learning enables therapeutic antibody optimization in mammalian cells by deciphering high-dimensional protein sequence space
(2019)bioRxivTherapeutic antibody optimization is time and resource intensive, largely because it requires low-throughput screening (103 variants) of full-length IgG in mammalian cells, typically resulting in only a few optimized leads. Here, we use deep learning to interrogate and predict antigen-specificity from a massively diverse sequence space to identify globally optimized antibody variants. Using a mammalian display platform and the therapeutic ...Working Paper -
Introducing UNSCdeb8 (beta)
(2019)SWP Working Paper: Research Division AsiaThe Working Papier introduces the database UNSCdeb8 (pronounced UNSC debate), which was developed within the project "Which region? The politics of the UN Security Council P5 in inter-national security crises". The project was jointly run by the Center for Security Studies at ETH Zürich, the Department of Geography and Environment at the University of Geneva, and the German Institute for International and Security Affairs (SWP). UNSCdeb8 ...Working Paper