08/2020 - ZeroCostDL4Mic: an open platform to use Deep-Learning in Microscopy
The resources and expertise needed to use Deep Learning (DL) in bioimaging remain significant barriers for most laboratories. We present https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki, a platform simplifying access to DL by exploiting the free, cloud-based computational resources of Google Colab. https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki allows researchers to train, evaluate, and apply key DL networks to perform tasks including segmentation, detection, denoising, restoration, resolution enhancement […]
08/2020 - Identification of Intrinsic Drug Resistance and Its Biomarkers in High-Throughput Pharmacogenomic and CRISPR Screens
High-throughput drug screens in cancer cell lines test compounds at low concentrations, thereby enabling the identification of drug-sensitivity biomarkers, while resistance biomarkers remain underexplored. Dissecting meaningful drug responses at high concentrations is challenging due to cytotoxicity, i.e., off-target effects, thus limiting resistance biomarker discovery to frequently mutated cancer genes. To address this, we interrogate subpopulations […]
08/2020 - Analysis of CRISPR‐Cas9 screens identify genetic dependencies in melanoma
Targeting the MAPK signaling pathway has transformed the treatment of metastatic melanoma. CRISPR‐Cas9 genetic screens provide a genome‐wide approach to uncover novel genetic dependencies that might serve as therapeutic targets. Here, we analyzed recently reported CRISPR‐Cas9 screens comparing data from 28 melanoma cell lines and 313 cell lines of other tumor types in order to […]
07/2020 - In-cell architecture of an actively transcribing-translating expressome
In bacteria, RNA polymerases can associate with ribosomes to form transcription-translation units called expressomes. Multiple models based on structural data of in vitro reconstitution assays have been proposed for how the two machineries interface with one another. Understanding this bacteria-specific coupling mechanism offers insight regarding the central dogma of molecular biology and might be leveraged […]
07/2020 - Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases
Being the recipient for huge public and private investments, the healthcare sector results to be an interesting target for fraudsters. Nowadays, the availability of a great amount of data makes it possible to tackle this issue with the adoption of data mining techniques. This approach can provide more efficient control of processes in terms of […]
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