A5100409799- Bioinformatics and Genomic Networks
- Complex Network Analysis Techniques
- Biomedical Text Mining and Ontologies
- Microbial Metabolic Engineering and Bioproduction
- Cell Image Analysis Techniques
- Adversarial Robustness in Machine Learning
- Microbial Metabolism and Applications
- Advanced Computing and Algorithms
- Recommender Systems and Techniques
- Cloud Data Security Solutions
- Machine Learning in Bioinformatics
- Immunotoxicology and immune responses
- Video Surveillance and Tracking Methods
- Bacterial Genetics and Biotechnology
- Random lasers and scattering media
- Data-Driven Disease Surveillance
- Face recognition and analysis
- Advanced Fluorescence Microscopy Techniques
- Bacillus and Francisella bacterial research
- Advanced Graph Neural Networks
- Optical Coherence Tomography Applications
- Data Stream Mining Techniques
- Cryptography and Data Security
- Face Recognition and Perception
- Blockchain Technology Applications and Security
Tianjin University
2024
Chongqing University of Posts and Telecommunications
2023
Google (United States)
2022
Qilu Hospital of Shandong University
2022
The University of Melbourne
2022
Winston-Salem State University
2013
In fighting the COVID-19 pandemic, main challenges include lack of prior research and urgency to find effective solutions. It is essential accurately rapidly summarize relevant work explore potential solutions for diagnosis, treatment prevention COVID-19. a daunting task numerous existing works assess their effectiveness. This paper explores discovery new approaches based on dynamic link prediction, which analyze topological network keywords predict possible connections concepts. A...
Abstract Motivation Protein-protein interactions (PPIs) are critical to normal cellular function and related many disease pathways. A range of protein functions mediated regulated by through post-translational modifications (PTM). However, only 4% PPIs annotated with PTMs in biological knowledge databases such as IntAct, mainly performed manual curation, which is neither time- nor cost-effective. Here we aim facilitate annotation extracting along their pairwise PTM from the literature using...
In this paper, we introduce a large scale online multi-task deep learning framework for modeling multiple feed ads auction prediction tasks on an industry-scale recommendation platform. Multiple are combined into one single model which is continuously trained real time new data. Multi-tasking models in real-time faces many real-world challenges. For example, each task may be different set of training data; the labels have arrival due to label delay; will interact with other; combining losses...
Person re-identification (re-ID) as a retrieval task often utilizes re-ranking model to improve performance. Existing methods are typically designed for conventional person re-ID with RGB images, while skeleton representation skeleton-based still remains be explored. To fill this gap, we revisit the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k$</tex-math></inline-formula> -reciprocal distance in...
A personal health record (PHR) system stores health-related information, which can assist physicians in quickly forming appropriate treatment plans emergency situations. Because a PHR contains lots of sensitive the patients are only willing to share their records with authorized doctors permission. There three main challenging issues: (1) it is costly store and maintain growing PHRs data; (2) existing systems still face privacy leakage risk during data transmission access control processes;...
Overlapped multi-focus light sheet (MF-LS) along beam propagation microscope has generated significant interest due to its reportedly superior axial resolving power when compared conventional Gaussian (GLS) systems. By axially overlapped multiple sheets in the illumination path, it would weld combined field of view (FOV) and be wider than stationary counterparts. However, effect diffractive energy entering focal space desired beam, impacting optical sectioning capabilities system not been...
Artificial neural networks (ANNs) are considered the current best models of biological vision. ANNs predictors activity in ventral stream; moreover, recent work has demonstrated that ANN fitted to neuronal can guide synthesis images drive pre-specified response patterns small populations. Despite success predicting and steering firing activity, these results have not been connected with perceptual or behavioral changes. Here we propose an array methods for creating minimal, targeted image...
Protein-protein interactions (PPIs) are critical to normal cellular function and related many disease pathways. However, only 4% of PPIs annotated with PTMs in biological knowledge databases such as IntAct, mainly performed through manual curation, which is neither time nor cost-effective. We use the IntAct PPI database create a distant supervised dataset interacting protein pairs, their corresponding PTM type, associated abstracts from PubMed database. train an ensemble BioBERT models -...
Reliable skin cancer diagnosis models play an essential role in early screening and medical intervention. Prevailing computer-aided classification systems employ deep learning approaches. However, recent studies reveal their extreme vulnerability to adversarial attacks -- often imperceptible perturbations significantly reduce the performances of models. To mitigate these threats, this work presents a simple, effective, resource-efficient defense framework by reverse engineering images....