Faisal Alquaddoomi
A5001950261- Bioinformatics and Genomic Networks
- Single-cell and spatial transcriptomics
- Green IT and Sustainability
- Cancer Genomics and Diagnostics
- Biomedical Text Mining and Ontologies
- Innovative Human-Technology Interaction
- Gene expression and cancer classification
- COVID-19 Digital Contact Tracing
- Genomics and Phylogenetic Studies
- Advanced Graph Neural Networks
- COVID-19 epidemiological studies
- Genomics and Rare Diseases
- Academic Publishing and Open Access
- Cell Image Analysis Techniques
- Misinformation and Its Impacts
- Context-Aware Activity Recognition Systems
- Gut microbiota and health
- BRCA gene mutations in cancer
- Spam and Phishing Detection
- Immune cells in cancer
- Cloud Computing and Resource Management
- Human Mobility and Location-Based Analysis
- Peer-to-Peer Network Technologies
- Recommender Systems and Techniques
- Personal Information Management and User Behavior
SIB Swiss Institute of Bioinformatics
2020-2024
Colorado School of Public Health
2023
ETH Zurich
2020-2023
University of Colorado Denver
2022-2023
University of Colorado Anschutz Medical Campus
2023
University of California, Los Angeles
2012-2018
University of Zurich
2018
University Hospital of Zurich
2018
UCLA Health
2013-2015
The BRCA Challenge is a long-term data-sharing project initiated within the Global Alliance for Genomics and Health (GA4GH) to aggregate BRCA1 BRCA2 data support highly collaborative research activities. Its goal generate an informed current understanding of impact genetic variation on cancer risk across iconic predisposition genes, BRCA2. Initially, reported variants in available from public databases were integrated into single, newly created site, www.brcaexchange.org. purpose Exchange...
Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing ontologies, semantic models, knowledge graphs translational research. App an integrated platform combining about genes, phenotypes, diseases across species. Monarch's APIs enable access to carefully...
Recent technological advances have led to an increase in the production and availability of single-cell data. The ability integrate a set multi-technology measurements would allow identification biologically or clinically meaningful observations through unification perspectives afforded by each technology. In most cases, however, profiling technologies consume used cells thus pairwise correspondences between datasets are lost. Due sheer size can acquire, scalable algorithms that able...
Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read RNA sequencing (scRNA-seq) on clinical samples from three ovarian patients presenting with omental metastasis and increase PacBio depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation protein-coding gene...
We present ohmage, a mobile to web platform that records, analyzes, and visualizes data from both prompted experience samples entered by the user, as well continuous streams of passively collected sensors onboard device. ohmage has been used in number research health stu
Participatory sensing (PS) is a distributed data collection and analysis approach where individuals, acting alone or in groups, use their personal mobile devices to systematically explore interesting aspects of lives communities [Burke et al. 2006]. These can be used capture diverse spatiotemporal through both intermittent self-report continuous recording from on-board sensors applications. Ohmage (http://ohmage.org) modular extensible open-source, Web PS platform that records, stores,...
We call upon the research community to standardize efforts use daily self-reported data about COVID-19 symptoms in response pandemic and form a collaborative consortium maximize global gain while protecting participant privacy.
CD8+ tumor-infiltrating T cells can be regarded as one of the most relevant predictive biomarkers in immune-oncology. Highly infiltrated tumors, referred to inflamed (clinically "hot"), show favorable response immune checkpoint inhibitors contrast tumors with a scarce infiltrate called desert or excluded "cold"). Nevertheless, quantitative and reproducible methods examining their prevalence within are lacking. We therefore established computational diagnostic algorithm quantitatively measure...
Smartphones can capture diverse spatio-temporal data about an individual; including both intermittent self-report, and continuous passive collection from onboard sensors applications. The resulting personal streams support powerful inference the user's state, behavior, well-being environment. However making sense acting on these multi-dimensional, heterogeneous requires iterative intensive exploration of datasets, development customized analysis techniques that are appropriate for a...
Deep single-cell multi-omic profiling offers a promising approach to understand and overcome drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML). Here, we combine ex vivo (pharmacoscopy) with bulk DNA, RNA, protein analyses, alongside clinical data from 21 rrAML patients. Unsupervised integration reveals reduced response the Bcl-2 inhibitor venetoclax (VEN) patients treated both hypomethylating agent (HMA) VEN, compared those pre-exposed chemotherapy HMA alone....
Studying proteins through the lens of evolution can reveal conserved features, lineage-specific variants, and their potential functions. MolEvolvR (https://jravilab.org/molevolvr) is a novel web-app enabling researchers to visualize molecular interest in phylogenetic context across tree life, spanning all superkingdoms. The accepts multiple input formats — protein/domain sequences, homologous proteins, or domain scans and, using general-purpose computational workflow, returns detailed...
Information is the most potent protective weapon we have to combat a pandemic, at both individual and global level. For individuals, information can help us make personal decisions provide sense of security. community, inform policy offer critical insights into epidemic COVID-19 disease. Fully leveraging power information, however, requires large amounts data access it. To achieve this, are making steps form an international consortium, Coronavirus Census Collective (CCC,...
Abstract Identifying cell types based on expression profiles is a pillar of single analysis. Existing machine-learning methods identify predictive features from annotated training data, which are often not available in early-stage studies. This can lead to overfitting and inferior performance when applied new data. To address these challenges we present scROSHI, utilizes previously obtained type-specific gene lists does require or the existence By respecting hierarchical nature type...
Abstract Background Hetnets, short for “heterogeneous networks,” contain multiple node and relationship types offer a way to encode biomedical knowledge. One such example, Hetionet, connects 11 of nodes—including genes, diseases, drugs, pathways, anatomical structures—with over 2 million edges 24 types. Previous work has demonstrated that supervised machine learning methods applied networks can identify drug repurposing opportunities. However, training set known relationships does not exist...
Multimodal profiling strategies promise to produce more informative insights into biomedical cohorts via the integration of information each modality contributes. To perform this integration, however, development novel analytical is needed. often come at expense lower sample numbers, which can challenge methods uncover shared signals across a cohort. Thus, factor analysis approaches are commonly used for high-dimensional data in molecular biology, they typically do not yield representations...
While we often think of words as having a fixed meaning that use to describe changing world, are also dynamic and changing. Scientific research can be remarkably fast-moving, with new concepts or approaches rapidly gaining mind share. We examined scientific writing, both preprint pre-publication peer-reviewed text, identify terms have changed examine their use. One particular challenge faced was the shift from closed open access publishing meant size available corpora by over an order...
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces B and T cell responses, contributing to virus neutralization. In a cohort of 2,911 young adults, we identified 65 individuals who had an asymptomatic or mildly symptomatic SARS-CoV-2 infection characterized their humoral responses the Spike (S), Nucleocapsid (N) Membrane (M) proteins. We found that previous induced CD4 cells vigorously responded pools peptides derived from S N By using statistical machine learning...
No abstract available.