Hassaan Maan's research while affiliated with University of Toronto and other places
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Publications (12)
Generative pre-trained models have achieved remarkable success in various domains such as natural language processing and computer vision. Specifically, the combination of large-scale diverse datasets and pre-trained transformers has emerged as a promising approach for developing foundation models. While texts are made up of words, cells can be cha...
A bstract
Single-cell sequencing has emerged as a promising technique to decode cellular heterogeneity and analyze gene functions. With the high throughput of modern techniques and resulting large-scale sequencing data, deep learning has been used extensively to learn representations of individual cells for downstream tasks. However, most existing...
Single-cell transcriptomic data measured across distinct samples has led to a surge in computational methods for data integration. Few studies have explicitly examined the common case of cell-type imbalance between datasets to be integrated, and none have characterized its impact on downstream analyses. To address this gap, we developed the Iniquit...
Macrophage colony stimulating factor-1 (CSF-1) plays a critical role in maintaining myeloid lineage cells. However, congenital global deficiency of CSF-1 (Csf1op/op) causes severe musculoskeletal defects that may indirectly affect hematopoiesis. Indeed, we show here that osteolineage-derived Csf1 prevented developmental abnormalities but had no eff...
The introduction of RNA velocity in single-cell studies has opened new ways of examining cell differentiation and tissue development. Existing RNA velocity estimation methods are based on strong assumptions of either complete observation of cells in steady states or a predefined dynamics pattern parameterized by constant coefficients. These assumpt...
The COVID-19 pandemic has highlighted the urgent need for the identification of new antiviral drug therapies for a variety of diseases. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2, while other related human coronaviruses cause diseases ranging from severe respiratory infections to the common cold. We developed a computatio...
Genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly important to monitor the transmission and adaptive evolution of the virus. The accessibility of high-throughput methods and polymerase chain reaction (PCR) has facilitated a growing ecosystem of protocols. Two differing protocols are tiling multiplex P...
Two highly pathogenic human coronaviruses that cause severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) have evolved proteins that can inhibit host antiviral responses, likely contributing to disease progression and high case-fatality rates. SARS-CoV-2 emerged in December 2019 resulting in a global pandemic. Recent...
Unfortunately the article was published with a spell error in the co-author name "Hassan Maan". The correct co-author name should be "Hassaan Maan".
Objective
To determine the interobserver variability of the 2015 American Thyroid Association (ATA) thyroid guidelines and to evaluate the diagnostic accuracy of the guidelines in detecting thyroid cancer.
Materials and methods
Sonographic patterns of 189 thyroid lesions were retrospectively analyzed by two radiologists according to the 2015 guide...
Citations
... Several models have been designed and trained on this data (e.g. scGPT [23], scFoundation [24], Geneformer [25]), with the goal of creating a foundation model for single cell transcriptomics data analogous to foundation models in natural language processing. ...
... In contrast, AtacAnnoR not only treats each reference cell type equally but also treats each query cell as an independent sample to compare with each reference cell type, rendering the annotation independent of the proportions of cell types in the reference or query datasets. Studies have shown that the imbalance between datasets could significantly impact the performance of methods on dataset integration [42,43]. Here, all competing methods except MASTERO and CellWalkR, which are marker-gene-based methods, rely on dataset integration in order to conduct the annotation. ...
... CSF-1 is secreted by various cell types, such as blood vessel endothelial cells (EC) and mesenchymal stromal cells (26), lymphatic endothelial cells (LEC) (27,28), fibroblasts (29) and neurons (30). However, CSF-1 expression is often localized to specific organized cellular milieus known as niches (31), and niche-specific depletion of CSF-1 leads to elimination of local resident macrophage subsets (28). ...
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... By this means, recently Cui et al. presented DeepVelo, a DNN-based approach that is empowered by deep GCN and reduced the restrictions of existing methods. DeepVelo can predict RNA cellular velocities without pre-defined kinetic patterns, as well as RNA velocities for high-complexity dynamics, especially for cell populations with many lineages and heterogeneous cell types [168]. ...
... The target proteins for the three compounds and carvone were predicted with the MatchMaker DTi prediction model [41] in Ligand Express. MatchMaker screens and ranks 8624 human proteins for complementarity. ...
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... Using molecular biology methods to identify SARS-CoV-2 variants was generally applied in surveillance and clinical diagnosis. Deep sequencing technology is widely utilized to identify SARS-CoV-2 variants, which can identify each mutation in the sample [37,38]. Real-time PCR assays for identifying SARS-CoV-2 variants were also reported [39,40]. ...
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... Interferon-related adaptations in bats include, e.g. constitutive and highly inducible expression, and expanded and divergent ranges of interferon-induced genes [18]. More generally, arms races of host interferon systems with viral anti-interferon tactics, in bats and other mammals, represent some of most diverse and complex molecular-conflictual interactions yet described, that lead to diverse outcomes in both bats and viruses that are expected to be specific to each host-virus interaction [19][20][21]. ...
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... Accordingly, the operation mode was set as homology-based misassembly correction. Coronavirus Typing Tool was used to further investigate the SARS-CoV-2 genotype, phylogenetic analysis, and mutation estimations among samples 20 . The lineage and distribution of samples were determined by Nestclade (https://clades.nextstrain.org/) ...
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... Based on our findings, interobserver agreement was insufficient for evaluation of nodule margins and moderate for microcalcifications, a clear difference compared to previous studies which found better agreement (19,(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49) using still images (Figure 2), while intraobserver variation was comparable (Figure 3). This is explained almost exclusively by the difference in observer-dependent interpretation of nodule characteristics; while microcalcification and taller-than-wide shape have clear definitions, this is less true for nodule margins. ...
