A5023791202- Genomics and Chromatin Dynamics
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Neural Networks and Applications
- Innovative Human-Technology Interaction
- Long-Term Effects of COVID-19
- Psychosomatic Disorders and Their Treatments
- Ethics and Social Impacts of AI
- Genomic variations and chromosomal abnormalities
- Lower Extremity Biomechanics and Pathologies
- Alcohol Consumption and Health Effects
- COVID-19 epidemiological studies
- COVID-19 and Mental Health
- Molecular Biology Techniques and Applications
- Genetics and Neurodevelopmental Disorders
- COVID-19 Pandemic Impacts
- SARS-CoV-2 and COVID-19 Research
- Substance Abuse Treatment and Outcomes
- CRISPR and Genetic Engineering
- Cancer-related molecular mechanisms research
- Balance, Gait, and Falls Prevention
British Columbia Children's Hospital
2020-2023
University of British Columbia
2020-2023
German Cancer Research Center
2022-2023
University of Ottawa
2023
European Molecular Biology Laboratory
2022
Institut Montpelliérain Alexander Grothendieck
2020-2022
Heidelberg University
2022
Institut de Génétique Moléculaire de Montpellier
2019-2021
Université de Montpellier
2019-2021
Centre National de la Recherche Scientifique
2020-2021
We collated contact tracing data from COVID-19 clusters in Singapore and Tianjin, China estimated the extent of pre-symptomatic transmission by estimating incubation periods serial intervals. The mean accounting for intermediate cases were 4.91 days (95%CI 4.35, 5.69) 7.54 6.76, 8.56) respectively. interval was 4.17 2.44, 5.89) 4.31 2.91, 5.72) (Singapore, Tianjin). intervals are shorter than periods, suggesting that may occur a large proportion events (0.4–0.5 0.6–0.8 our analysis with...
Abstract Background As the COVID-19 epidemic is spreading, incoming data allows us to quantify values of key variables that determine transmission and effort required control epidemic. We incubation period serial interval distribution for clusters in Singapore Tianjin. infer basic reproduction number identify extent pre-symptomatic transmission. Methods collected outbreak information from Tianjin, China, reported Jan.19-Feb.26 Jan.21-Feb.27, respectively. estimated periods intervals both...
We present Queer in AI as a case study for community-led participatory design AI. examine how and intersectional tenets started shaped this community's programs over the years. discuss different challenges that emerged process, look at ways organization has fallen short of operationalizing principles, then assess organization's impact. provides important lessons insights practitioners theorists methods broadly through its rejection hierarchy favor decentralization, success building aid by...
Abstract MYT1L is an autism spectrum disorder (ASD)-associated transcription factor that expressed in virtually all neurons throughout life. How mutations cause neurological phenotypes and whether they can be targeted remains enigmatic. Here, we examine the effects of deficiency human mice. Mutant mice exhibit neurodevelopmental delays with thinner cortices, behavioural phenotypes, gene expression changes resemble those ASD patients. target genes, including WNT NOTCH , are activated upon...
Deep learning models such as convolutional neural networks (CNNs) excel in genomic tasks but lack interpretability. We introduce ExplaiNN, which combines the expressiveness of CNNs with interpretability linear models. ExplaiNN can predict TF binding, chromatin accessibility, and de novo motifs, achieving performance comparable to state-of-the-art methods. Its predictions are transparent, providing global (cell state level) well local (individual sequence biological insights into data. serve...
Abstract Background Deep learning has proven to be a powerful technique for transcription factor (TF) binding prediction but requires large training datasets. Transfer can reduce the amount of data required deep learning, while improving overall model performance, compared separate each new task. Results We assess transfer strategy TF consisting pre-training step, wherein we train multi-task with multiple TFs, and fine-tuning initialize single-task models individual TFs weights learned by...
Using the Cap Analysis of Gene Expression (CAGE) technology, FANTOM5 consortium provided one most comprehensive maps transcription start sites (TSSs) in several species. Strikingly, ~72% them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs show that, all species studied, significant fraction CAGE peaks microsatellites, also called short tandem repeats (STRs). To confirm this transcription,...
Abstract Sequence-based deep learning models, particularly convolutional neural networks (CNNs), have shown superior performance on a wide range of genomic tasks. A key limitation these models is the lack interpretability, slowing down their adoption by genomics community. Current approaches to model interpretation do not readily reveal how makes predictions, can be computationally intensive, and depend implemented architecture. Here, we introduce ExplaiNN, an adaptation additive models[1]...
Abstract Background Deep learning has proven to be a powerful technique for transcription factor (TF) binding prediction, but requires large training datasets. Transfer can reduce the amount of data required deep learning, while improving overall model performance, compared separate each new task. Results We assess transfer strategy TF prediction consisting pre-training step, wherein we train multi-task with multiple TFs, and fine-tuning initialize single-task models individual TFs weights...
Abstract Background Using the Cap Analysis of Gene Expression technology, FANTOM5 consortium provided one most comprehensive maps Transcription Start Sites (TSSs) in several species. Strikingly, ~72% them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Results Here, we probe these unassigned TSSs show that, all species studied, significant fraction CAGE peaks short tandem repeats (STRs) corresponding homopolymers thymidines...
Using the Cap Analysis of Gene Expression (CAGE) technology, FANTOM5 consortium provided one most comprehensive maps Transcription Start Sites (TSSs) in several species. Strikingly, ~ 72% them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probed these unassigned TSSs showed that, all species studied, significant fraction CAGE peaks microsatellites, also called short tandem repeats (STRs). To confirm this...
We present Queer in AI as a case study for community-led participatory design AI. examine how and intersectional tenets started shaped this community's programs over the years. discuss different challenges that emerged process, look at ways organization has fallen short of operationalizing principles, then assess organization's impact. provides important lessons insights practitioners theorists methods broadly through its rejection hierarchy favor decentralization, success building aid by...