6 papers · 1 filter
MemNovo: Look Back at the Spectrum for Balanced De Novo Peptide Sequencing from Mass Spectrometry
Dongxin Lyu, Jingbo Zhou, Hongxin Xiang +2
De novo peptide sequencing from tandem mass spectrometry is pivotal in proteomics, enabling identification of novel peptides without reference databases. While recent Transformer-b…
Doloris: Dual Conditional Diffusion Implicit Bridges with Sparsity Masking Strategy for Unpaired Single-Cell Perturbation Estimation
Changxi Chi, Jun Xia, Yufei Huang +9
Estimating single-cell responses across various perturbations facilitates the identification of key genes and enhances drug screening, significantly boosting experimental efficienc…
VecFormer: Towards Efficient and Generalizable Graph Transformer with Graph Token Attention
Jingbo Zhou, Jun Xia, Siyuan Li +11
Graph Transformer has demonstrated impressive capabilities in the field of graph representation learning. However, existing approaches face two critical challenges: (1) most models…
Departures: Distributional Transport for Single-Cell Perturbation Prediction with Neural Schrödinger Bridges
Changxi Chi, Yufei Huang, Jun Xia +4
Predicting single-cell perturbation outcomes directly advances gene function analysis and facilitates drug candidate selection, making it a key driver of both basic and translation…
PRESCRIBE: Predicting Single-Cell Responses with Bayesian Estimation
Jiabei Cheng, Changxi Chi, Jingbo Zhou +2
In single-cell perturbation prediction, a central task is to forecast the effects of perturbing a gene unseen in the training data. The efficacy of such predictions depends on two…
NodeReg: Mitigating the Imbalance and Distribution Shift Effects in Semi-Supervised Node Classification via Norm Consistency
Shenzhi Yang, Jun Xia, Jingbo Zhou +2
Aggregating information from neighboring nodes benefits graph neural networks (GNNs) in semi-supervised node classification tasks. Nevertheless, this mechanism also renders nodes s…