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Found 33 papers, 2 papers with code
Drug resistance revealed by in silico deep mutational scanning and mutation tracker
As COVID-19 enters its fifth year, it continues to pose a significant global health threat, with the constantly mutating SARS-CoV-2 virus challenging drug effectiveness.
VRP-SAM: SAM with Visual Reference Prompt
In this paper, we propose a novel Visual Reference Prompt (VRP) encoder that empowers the Segment Anything Model (SAM) to utilize annotated reference images as prompts for segmentation, creating the VRP-SAM model.
PepHarmony: A Multi-View Contrastive Learning Framework for Integrated Sequence and Structure-Based Peptide Encoding
This study introduces a novel multi-view contrastive learning framework PepHarmony for the sequence-based peptide encoding task.
Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression
Evaluation results show our method improves visual quality by 14%, prompt alignment by 16. 2% and scene diversity by 15. 3%, compared to prompt engineering the base Emu model for stickers generation.
Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation
The Transformer, pretrained with hunderds of millions of protein sequences, embeds wild-type and mutant sequences, while persistent Laplacians track the topological invariant change and homotopic shape evolution induced by mutations in 3D protein structures, which are rendered from AlphaFold2.
Persistent topological Laplacian analysis of SARS-CoV-2 variants
Topological data analysis (TDA) is an emerging field in mathematics and data science.
D$^3$ETR: Decoder Distillation for Detection Transformer
Specifically, Adaptive Matching applies bipartite matching to adaptively match the outputs of the teacher and the student in each decoder layer, while Fixed Matching fixes the correspondence between the outputs of the teacher and the student with the same object queries, with the teacher's fixed object queries fed to the decoder of the student as an auxiliary group.
CAE v2: Context Autoencoder with CLIP Target
That is to say, the smaller the model, the lower the mask ratio needs to be.
Group DETR v2: Strong Object Detector with Encoder-Decoder Pretraining
The training process consists of self-supervised pretraining and finetuning a ViT-Huge encoder on ImageNet-1K, pretraining the detector on Object365, and finally finetuning it on COCO.
Ranked #8 on
Object Detection
on COCO test-dev
Emerging dominant SARS-CoV-2 variants
Accurate and reliable forecasting of emerging dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants enables policymakers and vaccine makers to get prepared for future waves of infections.
FedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection Systems
Deep learning (DL) methods have been widely applied to anomaly-based network intrusion detection system (NIDS) to detect malicious traffic.
A Generic Algorithm for Top-K On-Shelf Utility Mining
Compared with traditional utility mining, OSUM can find more practical and meaningful patterns in real-life applications.
Temporal Fuzzy Utility Maximization with Remaining Measure
In this paper, we propose a novel one-phase temporal fuzzy utility itemset mining approach called TFUM.
Itemset Utility Maximization with Correlation Measure
As an important data mining technology, high utility itemset mining (HUIM) is used to find out interesting but hidden information (e. g., profit and risk).
Smart System: Joint Utility and Frequency for Pattern Classification
Big data technologies such as design making, event detection, and classification are developed to help manufacturing organizations to achieve smart systems.
Persistent Laplacian projected Omicron BA.4 and BA.5 to become new dominating variants
In particular, BA. 4 and BA. 5 are about 36\% more infectious than BA. 2 and are projected to become new dominating variants by natural selection.
Mathematical artificial intelligence design of mutation-proof COVID-19 monoclonal antibodies
It is imperative to develop effective mutation-proof mAbs for treating COVID-19 patients infected by all emerging variants and/or the original SARS-CoV-2.
Omicron BA.2 (B.1.1.529.2): high potential to becoming the next dominating variant
The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly replaced the Delta variant as a dominating SARS-CoV-2 variant because of natural selection, which favors the variant with higher infectivity and stronger vaccine breakthrough ability.
Omicron (B.1.1.529): Infectivity, vaccine breakthrough, and antibody resistance
The latest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant Omicron (B. 1. 1. 529) has ushered panic responses around the world due to its contagious and vaccine escape mutations.
Anomaly Rule Detection in Sequence Data
Analyzing sequence data usually leads to the discovery of interesting patterns and then anomaly detection.
TargetUM: Targeted High-Utility Itemset Querying
The algorithm uses a lexicographic querying tree and three effective pruning strategies to improve the mining efficiency.
The evolution of the mechanisms of SARS-CoV-2 evolution revealing vaccine-resistant mutations in Europe and America
The importance of understanding SARS-CoV-2 evolution cannot be overemphasized.
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation
The learning process of intra- and inter-session transition dynamics are integrated, to preserve the underlying low- and high-level item relationships in a common latent space.
MLIMC: Machine learning-based implicit-solvent Monte Carlo
Monte Carlo (MC) methods are important computational tools for molecular structure optimizations and predictions.
Review of the mechanisms of SARS-CoV-2 evolution and transmission
We anticipate that viral evolution will combine RBD co-mutations at these two sites, creating future variants that are tens of times more infectious than the original SARS-CoV-2.
Emerging vaccine-breakthrough SARS-CoV-2 variants
The molecular mechanism underlying such surge is elusive due to 4, 653 non-degenerate mutations on the spike protein, which is the target of most COVID-19 vaccines.
Practical and Configurable Network Traffic Classification Using Probabilistic Machine Learning
Network traffic classification that is widely applicable and highly accurate is valuable for many network security and management tasks.
Vaccine-escape and fast-growing mutations in the United Kingdom, the United States, Singapore, Spain, South Africa, and other COVID-19-devastated countries
We further unveil that mutation N501Y involved in United Kingdom (UK), South Africa, and Brazil variants may moderately weaken the binding between the RBD and many known antibodies, while mutations E484K and K417N found in South Africa and Brazilian variants can potentially disrupt the binding between the RDB and many known antibodies.
Methodology-centered review of molecular modeling, simulation, and prediction of SARS-CoV-2
To provide the reader a quick update about the status of molecular modeling, simulation, and prediction of SARS-CoV-2, we present a comprehensive and systematic methodology-centered narrative in the nick of time.
On the Construction of a Post-Quantum Blockchain for Smart City
In addition, traditional proof of work (PoW)-based consensus protocols such as Bitcoin cannot supply memory mining, and the transaction capacity of each block in a blockchain is limited and needs to be expanded.
Cryptography and Security
Prediction and mitigation of mutation threats to COVID-19 vaccines and antibody therapies
This discovery implies the vulnerability of current vaccines and antibody drugs to new mutations.
Characterizing SARS-CoV-2 mutations in the United States
Using genotyping, sequence-alignment, time-evolution, $k$-means clustering, protein-folding stability, algebraic topology, and network theory, we reveal that the US SARS-CoV-2 has four substrains and five top US SARS-CoV-2 mutations were first detected in China (2 cases), Singapore (2 cases), and the United Kingdom (1 case).
A Books Recommendation Approach Based on Online Bookstore Data
In the era of information explosion, facing complex information, it is difficult for users to choose the information of interest, and businesses also need detailed information on ways to let the ad stand out.
