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T-cells are central to SARS-CoV-2 clearance and immunological memory, yet their contribution to the persistence of post-acute sequelae of COVID-19 (PASC) remains poorly understood. The immunological features that distinguish individuals who…

The study of cells and their responses to genetic or chemical perturbations promises to accelerate the discovery of therapeutic targets. However, designing adequate and insightful models for such data is difficult because the response of a…

Machine Learning · Computer Science 2024-12-04 Haiyi Mao , Romain Lopez , Kai Liu , Jan-Christian Hütter , David Richmond , Panayiotis V. Benos , Lin Qiu

COVID-19 is a global pandemic caused by the SARS-CoV-2 coronavirus. T cells play a key role in the adaptive antiviral immune response by killing infected cells and facilitating the selection of virus-specific antibodies. However neither the…

The identification and validation of therapeutic antibodies is critical for developing effective treatments for many diseases. We present a computational approach for identifying antibodies targeting GFRAL-specific receptors, receptors…

Therapeutic modulation of immune states is central to the treatment of human disease. However, how drugs and drug combinations impact the diverse cell types in the human immune system remains poorly understood at the transcriptome scale.…

Chronic diseases are long-lasting conditions that require lifelong medical attention. Using big EMR data, we have developed early disease risk prediction models for five common chronic diseases: diabetes, hypertension, CKD, COPD, and…

Machine Learning · Computer Science 2026-03-13 Shaheer Ahmad Khan , Muhammad Usamah Shahid , Muddassar Farooq

Unsupervised cell type identification is crucial for uncovering and characterizing heterogeneous populations in single cell omics studies. Although a range of clustering methods have been developed, most focus exclusively on intrinsic…

Artificial Intelligence · Computer Science 2025-12-12 Liang Peng , Haopeng Liu , Yixuan Ye , Cheng Liu , Wenjun Shen , Si Wu , Hau-San Wong

Objective: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive…

Computation and Language · Computer Science 2025-04-09 Jie Pan , Seungwon Lee , Cheligeer Cheligeer , Elliot A. Martin , Kiarash Riazi , Hude Quan , Na Li

Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without…

Serology testing can identify past infection by quantifying the immune response of an infected individual providing important public health guidance. Individual immune responses are time-dependent, which is reflected in antibody…

Quantitative Methods · Quantitative Biology 2022-08-04 Prajakta Bedekar , Anthony J. Kearsley , Paul N. Patrone

The comorbidities of hypertension impose a heavy burden on patients and society. Early identification is necessary to prompt intervention, but it remains a challenging task. This study aims to address this challenge by combining joint graph…

Machine Learning · Computer Science 2025-06-13 Leming Zhou , Zuo Wang , Zhixuan Duan

Designing full-length, epitope-specific TCR {\alpha}\b{eta} remains challenging due to vast sequence space, data biases and incomplete modeling of immunogenetic constraints. We present LSMTCR, a scalable multi-architecture framework that…

Computational Engineering, Finance, and Science · Computer Science 2025-10-09 Ruihao Zhang , Xiao Liu

Antibodies are proteins produced by the immune system that can identify and neutralise a wide variety of antigens with high specificity and affinity, and constitute the most successful class of biotherapeutics. With the advent of…

Biomolecules · Quantitative Biology 2024-03-27 Henry Kenlay , Frédéric A. Dreyer , Aleksandr Kovaltsuk , Dom Miketa , Douglas Pires , Charlotte M. Deane

Antibodies comprise the most versatile class of binding molecules, with numerous applications in biomedicine. Computational design of antibodies involves generating novel and diverse sequences, while maintaining structural consistency.…

Biomolecules · Quantitative Biology 2023-06-21 Igor Melnyk , Vijil Chenthamarakshan , Pin-Yu Chen , Payel Das , Amit Dhurandhar , Inkit Padhi , Devleena Das

Motivation: The activity of the adaptive immune system is governed by T-cells and their specific T-cell receptors (TCR), which selectively recognize foreign antigens. Recent advances in experimental techniques have enabled sequencing of…

Biomolecules · Quantitative Biology 2023-08-28 Anna Weber , Jannis Born , María Rodríguez Martínez

High-throughput sequencing of T- and B-cell receptors makes it possible to track immune repertoires across time, in different tissues, in acute and chronic diseases and in healthy individuals. However quantitative comparison between…

Relation Classification (RC) in biomedical texts is essential for constructing knowledge graphs and enabling applications such as drug repurposing and clinical decision-making. We propose an error-aware teacher--student framework that…

Computation and Language · Computer Science 2025-07-22 Sinchani Chakraborty , Sudeshna Sarkar , Pawan Goyal

In this paper, several advanced data-driven nonlinear identification techniques are compared on a specific problem: a simplified glucoregulatory system modeling example. This problem represents a challenge in the development of an…

Systems and Control · Computer Science 2018-04-20 Anna Marconato , Maarten Schoukens , Koen Tiels , W. Dhammika Widanage , Amjad Abu-Rmileh , Johan Schoukens

Antibodies are versatile proteins that bind to pathogens like viruses and stimulate the adaptive immune system. The specificity of antibody binding is determined by complementarity-determining regions (CDRs) at the tips of these Y-shaped…

Biomolecules · Quantitative Biology 2022-01-31 Wengong Jin , Jeremy Wohlwend , Regina Barzilay , Tommi Jaakkola

All people with diabetes have the risk of developing diabetic retinopathy (DR), a vision-threatening complication. Early detection and timely treatment can reduce the occurrence of blindness due to DR. Computer-aided diagnosis has the…

Computer Vision and Pattern Recognition · Computer Science 2017-04-06 Ragav Venkatesan , Parag S. Chandakkar , Baoxin Li
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