Biology subjects

Gilbert, L.

Publications and source records attributed to Gilbert, L..

3 recordsLinked to original sources

bioRxiv2021

A global cancer data integrator reveals principles of synthetic lethality, sex disparity and immunotherapy.

Advances in cancer biology are increasingly dependent on integration of heterogeneous datasets. Large scale efforts have systematically mapped many aspects of cancer cell biology; however, it remains challenging for individual scientists to effectively integrate and understand this data. We have developed a new data retrieval and indexing framework that allows us to integrate publicly available data from different sources and to combine publicly available data with new or bespoke datasets. Beyond a database search, our approach empowered testable hypotheses of new synthetic lethal gene pairs, genes associated with sex disparity, and immunotherapy targets in cancer. Our approach is straightforward to implement, well documented and is continuously updated which should enable individual users to take full advantage of efforts to map cancer cell biology.

bioinformatics↗

bioRxiv2020

A common genetic architecture enables the lossy compression of large CRISPR libraries

There are thousands of ubiquitously expressed mammalian genes, yet a genetic knockout can be lethal to one cell, and harmless to another. This context specificity confounds our understanding of genetics and cell biology. 2 large collections of pooled CRISPR screens offer an exciting opportunity to explore cell specificity. One explanation, synthetic lethality, occurs when a single "private" mutation creates a unique genetic dependency. However, by fitting thousands of machine learning models across millions of omic and CRISPR features, we discovered a "public" genetic architecture that is common across cell lines and explains more context specificity than synthetic lethality. This common architecture is built on CRISPR loss-of-function phenotypes that are surprisingly predictive of other loss-of-function phenotypes. Using these insights and inspired by the in silico lossy compression of images, we use machine learning to identify small "lossy compression" sets of in vitro CRISPR constructs where reduced measurements produce genome-scale loss-of-function predictions.

systems biology↗

bioRxiv2020

Emergence of Lyme disease on treeless islands in Scotland, UK

Lyme disease (LD) is typically associated with forested habitats but has recently emerged on treeless islands in the Western Isles of Scotland. This has created a need to understand the environmental and human components of LD risk in open habitats. This study quantified both elements of LD risk and compared these between treeless islands with high and low LD incidence. We found high LD incidence was linked to higher prevalence in ticks (6.4% vs 0.4%) and increased human tick bite exposure. Most reported tick bites (72.7%) were within 1km of the home address and commonly in gardens. Residents on islands with high LD incidence reported increasing problems with ticks and suggested changing deer distribution as a potential driver. This study highlights the benefits to public health of an integrated approach to understand the factors contributing to LD emergence and a need to evaluate LD ecology in treeless habitats more broadly.

ecology↗