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ORCIDBIBM 2022: Las Vegas, NV, USA
- Donald A. Adjeroh, Qi Long, Xinghua Mindy Shi, Fei Guo, Xiaohua Hu, Srinivas Aluru, Giri Narasimhan, Jianxin Wang, Mingon Kang, Ananda Mondal, Jin Liu:
IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Las Vegas, NV, USA, December 6-8, 2022. IEEE 2022, ISBN 978-1-6654-6819-0 - Xiaoyi Guo, Yuqing Qian, Prayag Tiwari
, Quan Zou, Yijie Ding:
Kernel Risk Sensitive Loss-based Echo State Networks for Predicting Therapeutic Peptides with Sparse Learning. 6-11 - Zhijian Huang, Rongtao Zheng, Lei Deng:
DeepFusionGO: Protein function prediction by fusing heterogeneous features through deep learning. 12-17 - Tong Liu, Zheng Wang:
ST-ChIP: Accurate prediction of spatiotemporal ChIP-seq data with recurrent neural networks. 18-25 - Jinsheng Shang, Qihong Jiao, Cheng Chen, Daming Zhu, Xuefeng Cui:
Pretraining Transformers for TCR-pMHC Binding Prediction. 26-31 - Jyotsna Talreja Wassan, Haiying Wang, Huiru Zheng:
A New Phylogeny-Driven Random Forest-Based Classification Approach for Functional Metagenomics. 32-37 - Guolun Zhong, Lei Deng:
inACP: An integrated approach to the prediction of anticancer peptides. 38-43 - Xiangfei Zhou, Zhenqi Shi, Yingfu Wu, Jin Zhao, Hao Wu:
scHiCSC: A Novel Single-Cell Hi-C Clustering Framework by Contact-Weight-Based Smoothing and Feature Fusion. 44-50 - Kyudam Choi, Yurim Lee, Cheongwon Kim:
GCL-GO: A novel sequence-based hierarchy-aware method for protein function prediction. 51-56 - Yangyue Fang, Chaojian Zhang, Yu Fu, Tao Xue:
Learning spatial structures and network correlations improves unknown protein-protein interaction prediction. 57-62 - Tiantian Li, Daming Zhu, Haitao Jiang, Haodi Feng, Xuefeng Cui:
Longest k-tuple Common Sub-Strings. 63-66 - Weipeng Lv, Changkun Jiang, Jianqiang Li:
MSE-CapsPPISP: Spatial Hierarchical Protein-Protein Interaction Sites Prediction Using Squeeze-and-Excitation Capsule Networks. 67-72 - Nazifa Ahmed Moumi, Connor L. Brown, Peter J. Vikesland, Amy Pruden, Liqing Zhang:
Protein-Protein Interaction Network Analysis Reveals Distinct Patterns of Antibiotic Resistance Genes. 73-76 - Hoai-Nhan Tran, Phuc-Xuan-Quynh Nguyen, Xiaoqing Peng, Jianxin Wang:
An integration of deep learning with feature fusion for protein-protein interaction prediction. 77-80 - Xiaoting Wang, Juan Wang, Haodong Bian, Maozu Guo:
Sub-Loc: predicting protein sub-mitochondrial localization based on sequence embedding. 81-85 - Zeyu Wang, Tao Lin, Xiaoli Yang, Yanchun Liang, Xiaohu Shi:
Protein Subcellular Localization Prediction by Combining ProtBert and BiGRU. 86-89 - Yingwen Zhao, Zhihao Yang, Yongkai Hong, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang:
Adaptive Multi-view Graph Convolutional Network for Gene Ontology Annotations of Proteins. 90-93 - Yang Li, Xue-Gang Hu, Pei-Pei Li, Lei Wang, Zhu-Hong You:
Predicting circRNA-disease associations using similarity assessing graph convolution from multi-source information networks. 94-101 - Jiawei Li, Fan Yang, Fang Wang, Yu Rong, Peilin Zhao, Shizhan Chen, Jianhua Yao, Jijun Tang, Fei Guo:
Integrating Prior Knowledge with Graph Encoder for Gene Regulatory Inference from Single-cell RNA-Seq Data. 102-107 - Gongxu Luo, Chenyang Li, Hejie Cui, Lichao Sun, Lifang He, Carl Yang:
Multi-View Brain Network Analysis with Cross-View Missing Network Generation. 108-115 - Haojiang Tan, Jun Wang, Guoxian Yu, Wei Guo, Maozu Guo:
Phenotype Prediction by Heterogeneous Molecular Network Embedding. 116-121 - Song Wang, Xiao-Tai Huang, Kei Hang Katie Chan, Lin Gao:
IMRDriver: coding and non-coding cancer driver genes identification based on network propagation. 122-129 - Tao Wang, Hui Zhao, Yifu Xiao, Hanzi Yang, Xipeng Yin, Yongtian Wang, Bing Xiao, Xuequn Shang, Jiajie Peng:
Discovering eQTL Regulatory Patterns Through eQTLMotif. 130-135 - Nana Wei, Yijing Zhu, Yating Nie, Shiyu Fan, Yuanchen Sun, Xiaoqi Zheng:
Purification of tumor methylomes through residual decomposition. 136-141 - Hang Wei, Xiayue Fan, Shuai Wu:
iCircDA-ENR: identification of circRNA-disease associations based on ensemble network representation. 142-147 - Alexander Gerniers, Pierre Dupont:
MicroCellClust 2: a hybrid approach for multivariate rare cell mining in large-scale single-cell data. 148-153 - Pei Li, Ying Xiao, Weizhong Zhao, Xingpeng Jiang, Xianjun Shen:
Inferring microbe-metabolite interactions by heterogeneous network fusion based on graph convolution network. 154-157 - Yajun Liu, Yulian Ding, Aimin Li, Rong Fei, Guo Xie, Fang-Xiang Wu:
Prediction of exosomal piRNAs based on deep learning for sequence embedding with attention mechanism. 158-161 - Roland Madadjim, Haluk Dogan, Juan Cui:
Computational learning of small RNA regulation in pancreatic cancer progression. 162-167 - Lihong Peng, Liangliang Huang, Yuankang Lu, Guangyi Liu, Min Chen, Guosheng Han:
Identifying possible lncRNA-disease associations based on deep learning and positive-unlabeled learning. 168-173 - Bingbo Wang, Chao Han, Xiujuan Ma:
Network Connectivity Analysis of Coding and Noncoding RNAs in Cancer. 174-177 - Zehao Xiong, Xiangtao Chen, Jiawei Luo, Cong Shen, Zhongyuan Xu:
scSAGAN: A scRNA-seq data imputation method based on Semi-Supervised Learning and Probabilistic Latent Semantic Analysis. 178-181 - Fengqi Zhong, Yuansong Zeng, Yubao Liu, Yuedong Yang:
SCdenoise: a reference-based scRNA-seq denoising method using semi-supervised learning. 182-185 - Wenjian Zhou, Ji Lu, Xiwei Tang:
A Transformer-based Model for Plant miRNA-lncRNA Interaction Prediction. 186-189 - Lingzhi Zhu, Kai Zheng, Guihua Duan, Jianxin Wang:
Prediction of virus-receptor interactions based on multi-view learning and link prediction. 190-193 - Siqi Chen, Ruiqing Zheng, Luyi Tian, Fang-Xiang Wu, Min Li:
BayesImpute: a Bayesian imputation method for single-cell RNA-seq data. 194-199 - Jing Gao, Fa Zhang, Kai Hu, Xuefeng Cui:
Hexagonal Convolutional Neural Network for Spatial Transcriptomics Classification. 200-205 - Wei Lan, Jin Ye, Xun Sun, Xiaoshu Zhu, Qingfeng Chen, Yi Pan:
scIAC: clustering scATAC-seq data based on Student's t-distribution similarity imputation and denoising autoencoder. 206-211 - Fangting Li, Yuhai Zhao, Boxin Guan, Yuan Li:
A Distributed Evolutionary Framework for Large-scale SNP-SNP Interaction Detection. 212-219 - Yadong Liu, Zhongyu Liu, Tao Jiang, Tianyi Zang, Yadong Wang:
Comparison of the Nanopore and PacBio sequencing technologies for DNA 5-methylcytosine detection. 220-225 - Zixiang Pan, Yuansong Zeng, Yuefan Lin, Weijiang Yu, Haokun Zhang, Yuedong Yang:
A Meta-learning based Graph-Hierarchical Clustering Method for Single Cell RNA-Seq Data. 226-232 - Carlos Soto, Darshan W. Bryner, Audrey Dalgarno, Nicola Neretti, Anuj Srivastava:
TADBay: A Bayesian Construction of Topologically Associated Domains. 233-240 - Xinfeng Wang, Haoyang Zhang, Xuehao Xiu, Mengling Qi, Yuedong Yang, Huiying Zhao:
Genetic and phenotypic relationships between coronary atherosclerotic heart disease and electrocardiographic traits. 241-246 - Ziwei Xu, Ruiqing Zheng, Yuxuan Chen, Edwin Wang, Min Li:
A single cell potency inference method based on the local cell-specific network entropy. 247-252 - Jiaqian Yan, Jianing Xi, Zhenhua Yu:
A parametric model for clustering single-cell mutation data. 253-260 - Ohhyeon Kwon, Maree J. Webster, Sanghyeon Kim, Doheon Lee:
SNEP-DB: An integrated database to associate genomic and pathological aspects of psychiatric disorders. 261-265 - Jiancheng Li, Chongle Pan, Xuan Guo:
IDIA: An Integrative Signal Extractor for Data-Independent Acquisition Proteomics. 266-269 - Yue Liu, Junfeng Zhang, Shulin Wang, Wei Zhang, Xiangxiang Zeng, Chee Keong Kwoh:
A heterogeneous graph cross-omics attention model for single-cell representation learning. 270-275 - Zepeng Liu, Xiao-Tai Huang, Kei Hang Katie Chan, Lin Gao:
Predicting the functional effects of human non-coding variants based on stacking ensemble learning. 276-280 - Lihong Peng, Xianzhi He, Li Zhang, Xinhuai Peng, Yuankang Lu, Zejun Li, Xing Chen:
A deep learning-based unsupervised learning method for spatially resolved transcriptomic data analysist. 281-286 - Shengze Wang, Shichao Feng, Chongle Pan, Xuan Guo:
FineFDR: Fine-grained Taxonomy-specific False Discovery Rates Control in Metaproteomics. 287-292 - Weiming Xiang, Yingbo Cui, Yaning Yang, Ang Zhang, Boya Ji, Shaoliang Peng:
MSVF: Multi-task Structure Variation Filter with Transfer Learning in High-throughput Sequencing. 293-296 - Shoujia Zhang, Wei Li, Weidong Xie, Linjie Wang:
Feature Selection for Microarray Data via Community Detection Fusing Multiple Gene Relation Networks Information. 297-302 - Yu Zhang, Chenchen Li, Haodi Feng, Daming Zhu:
DLmeta: a deep learning method for metagenomic identification. 303-308 - Jiamin Chen, Zhenpeng Wu, Jianliang Gao, Xiaohua Hu:
Glycan Immunogenicity Prediction with Efficient Automatic Graph Neural Network. 309-314 - Zhiyuan Chen, Xiaomin Fang, Zixu Hua, Yueyang Huang, Fan Wang, Hua Wu:
HelixMO: Sample-Efficient Molecular Optimization in Scene-Sensitive Latent Space. 315-321 - Xu Gong, Maotao Liu, Haichao Sun, Min Li, Qun Liu:
HS-DTI: Drug-target Interaction Prediction Based on Hierarchical Networks and Multi-order Sequence Effect. 322-327 - Linyuan Guo, Jianxin Wang:
ViTRMSE: a three-dimensional RMSE scoring method for protein-ligand docking models based on Vision Transformer. 328-333 - Peiying Li, Boheng Cao, Shikui Tu, Lei Xu:
RecurPocket: Recurrent Lmser Network with Gating Mechanism for Protein Binding Site Detection. 334-339 - Ziyan Wang, Chengzhi Hong, Xuan Liu, Zhankun Xiong, Feng Liu, Wen Zhang:
Predicting drug transcriptional response similarity using Signed Graph Convolutional Network. 340-345 - Han Wang, Hangxu Zhu, Wenhao Li, Ming Liu, Li Zhang, Dong Xu:
Predicting Compound-Protein Interaction by Deepening the Systemic Background via Molecular Network Feature Embedding. 346-353 - Zhengwei Wang, Yuxiao Wang, Xuan Zhang, Zhaoxu Meng, Zhenghe Yang, Wei Zhao, Xuefeng Cui:
Graph-based Reaction Classification by Contrasting between Precursors and Products. 354-359 - Jingxuan Wang, Zongzhao Qiu, Xuan Zhang, Zhenghe Yang, Wei Zhao, Xuefeng Cui:
Boosting Deep Learning-based Docking with Cross-attention and Centrality Embedding. 360-365 - Jinyong Wen, Yuhu Wang, Chunxia Zhang, Shiming Xiang, Chunhong Pan:
Discriminative Graph Representation Learning with Distributed Sampling. 366-373 - Xuan Zhang, Cheng Chen, Zhaoxu Meng, Zhenghe Yang, Haitao Jiang, Xuefeng Cui:
CoAtGIN: Marrying Convolution and Attention for Graph-based Molecule Property Prediction. 374-379 - Justin Jose, Ujjaini Alam, Divye Singh, Nidhi Jatana, Pooja Arora:
PandoraRL: DQN and Graph Convolution based ligand pose learning for SARS-COV1 Mprotease. 380-385 - Maotao Liu, Yifan Yang, Xu Gong, Li Liu, Qun Liu:
HierMRL: Hierarchical Structure-Aware Molecular Representation Learning for Property Prediction. 386-389 - Dongning Ma, Rahul Thapa, Xun Jiao:
MoleHD: Efficient Drug Discovery using Brain Inspired Hyperdimensional Computing. 390-393 - Yan Sun, Md. Mohaiminul Islam, Ehsan Zahedi, Mélaine Kuenemann, Hassan Chouaib, Pingzhao Hu:
Molecular Property Prediction based on Bimodal Supervised Contrastive Learning. 394-397 - Norah Saeed Awn, Yiming Li, Baoying Zhao, Min Zeng, Min Li:
LDAGSO: Predicting 1ncRNA-Disease Associations from Graph Sequences and Disease Ontology via Deep Learning techniques. 398-403 - Peng Chen, Jian Wang, Hongfei Lin, Yichen Wang, Di Zhao, Yijia Zhang:
Syntactic Type-aware Graph Attention Network for Drug-drug Interactions and their Adverse Effects Extraction. 404-409 - Mingliang Dou, Han Han, Genlang Chen, Fei Guo, Jijun Tang:
BP-DDI: Drug-drug interaction prediction based on biological information and pharmacological text. 410-415 - Junwen Duan, Huai Guo, Min Zeng, Jianxin Wang:
ASNet: An Adversarial Sparse Network for Multi-task Biomedical Named Entity Recognition. 416-421 - Haiyan Gong, Yi Yang, Xiaotong Zhang, Fuqiang Ma, Minghong Li, Zhengyuan Chen, Sichen Zhang, Yang Chen:
NeRV-3D-DC: A Nonlinear Dimensionality Reduction Visualization Method for 3D Chromosome Structure Reconstruction with High Resolution Hi-C Data. 422-429 - Yaowen Gu, Si Zheng, Bowen Zhang, Hongyu Kang, Jiao Li:
MilGNet: A Multi-instance Learning-based Heterogeneous Graph Network for Drug repositioning. 430-437 - Yuyang Huang, Shiwen Dong, Dandan Wang, Chunling Wan, Yang Yang:
Learning Time-Series Images of Niacin Skin-Flushing Test for the Diagnosis of Schizophrenia and Affective Disorder. 438-443 - Sidharth S. Jain, Megan E. Barefoot, Rency S. Varghese, Habtom W. Ressom:
Cell-type Deconvolution and Age Estimation Using DNA Methylation Reveals NK Cell Deficiency in the Hepatocellular Carcinoma Microenvironment. 444-449 - Yuxin Kang, Hansheng Li, Xuan Zhao, Xiaoshuang Shi, Feihong Liu, Qingguo Yan, Ying Guo, Lei Cui, Jun Feng, Lin Yang:
Invariant Content Synergistic Learning for Domain Generalization on Medical Image Segmentation. 450-456 - Seokwoo Lee, Myounghoon Cho, Wook Lee, Byungkyu Park, Kyungsook Han:
Predicting Lymph Node Metastasis and Distant Metastasis using Differential Correlations of miRNAs and Their Target RNAs in Cancer. 457-463 - Mei Li, Sihan Xu, Xiangrui Cai, Zhong Zhang, Hua Ji:
Contrastive Meta-Learning for Drug-Target Binding Affinity Prediction. 464-470 - Xingyi Li, Zhelin Zhao, Ju Xiang, Jialu Hu, Xuequn Shang:
A multi-source fusion method to identify biomarkers for breast cancer prognosis based on dual-layer heterogeneous network. 471-476 - Xingwang Li, Yijia Zhang, Jian Wang, Mingyu Lu, Hongfei Lin:
Knowledge-Enhanced Dual Graph Neural Network for Robust Medicine Recommendation. 477-482 - Xue Li, Yang Yang, Mingchen Ye, Yi Guan, Xuehui Yu, Jingchi Jiang:
Unified Fine-Grained Biomedical Entity Recognition as a Combination of Boundary Detection and Sequence Generation. 483-490 - Hai Liu, Hong-Dong Li:
KL-RF: Predicting disease-gene associations with model fusion. 491-496 - Yuting Lu, Yan Wang, Nan Sheng, Hao Wang, Yuan Fu, Yuan Tian:
RDDriver: A novel method based on multi-layer heterogeneous transcriptional regulation network for identifying pancreatic cancer biomarker. 497-502 - Ying Lv, Xiaodong Yue, Zhikang Xu, Yufei Chen, Zihao Li:
Selecting Reliable Instances from ImageNet for Medical Image Domain Adaptation. 503-508 - Qin Ma, Lin Zeng, Shikui Tu, Lei Xu:
Kernel Mean Matching with Mahalanobis Distance for Causal Inference of Time-to-event Outcome. 509-514 - Lihong Peng, Ruya Yuan, Chendi Han, Jingwei Tan, Zhao Wang, Min Chen, Xing Chen:
Analyses of cell-to-cell communication combining a heterogeneous deep ensemble framework and scoring approaches from single-cell RNA sequencing data. 515-522 - Wei Peng, Piaofang Yu, Wei Dai, Xiaodong Fu, Li Liu, Yi Pan:
Identification of personalized driver genes for individuals using graph convolution network. 523-528 - Wei Qian, Chenxu Zhao, Huajie Shao, Minghan Chen, Fei Wang, Mengdi Huai:
Patient Similarity Learning with Selective Forgetting. 529-534 - Yuening Qu, Chengxin He, Jin Yin, Zhenjiang Zhao, Jingyu Chen, Lei Duan:
MOVE: Integrating Multi-source Information for Predicting DTI via Cross-view Contrastive Learning. 535-540 - Jiahang Sha, Jingxuan Bao, Kefei Liu, Shu Yang, Zixuan Wen, Yuhan Cui, Junhao Wen, Christos Davatzikos, Jason H. Moore, Andrew J. Saykin, Qi Long, Li Shen:
Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. 541-548 - Junliang Shang, Yijun Gu, Yan Sun, Feng Li, Jin-Xin Liu, Boxin Guan:
Artificial bee colony algorithm based on self-adjusting random grouping for high-order epistasis detection. 549-554 - Jia-Hao Song, Cui-Xiang Lin, Hong-Dong Li:
An Alzheimer's disease gene prediction method based on ensemble of genome-wide association study summary statistics. 555-560 - Xian Tan, Yiping Sun, Shijie Fan, Yanhe Wang, Jingbo Zhang, Pingping Sun, Zhiqiang Ma:
DSHP: A Novel Sequence Based Deep Learning Prediction Model for HPV Integration Site. 561-566 - Jianfeng Wang, Shuokang Huang, Huifang Du, Yu Qin, Haofen Wang, Wenqiang Zhang:
MHKD-MVQA: Multimodal Hierarchical Knowledge Distillation for Medical Visual Question Answering. 567-574 - Lianzhi Wang, Cheng Liang, Wenjiao Dong, Wenlan Chen:
Multi-view Unsupervised Feature Selection via Consensus Guided Low-rank Tensor Learning. 575-580 - Han Wang, Jianwei Niu, Xuefeng Liu, Yong Wang:
Embracing Uniqueness: Generating Radiology Reports via a Transformer with Graph-based Distinctive Attention. 581-588 - Zixuan Wang, Yongqing Zhang, Yun Yu, Maocheng Wang, Yuhang Liu, Quan Zou:
Single-cell TF-DNA binding prediction and analysis based on transfer learning framework. 589-594 - Haiyan Wang, Jiazhou Chen, Bin Zhang, Hongmin Cai:
Accurate Multi-view Clustering by Exploiting Within-view High-order Affinities through Tensor Self-representation. 595-600 - Hong Wang, Xiaoqi Wang, Wenjuan Liu, Xiaolan Xie, Shaoliang Peng:
deepDGA: Biomedical Heterogeneous Network-based Deep Learning Framework for Disease-Gene Association Predictions. 601-606 - Wen-Yu Xi, Qianqian Ren, Jin-Xing Liu, Ying-Lian Gao:
HSAELDA: Predicting lncRNA-disease associations based on heterogeneous networks and Stacked Autoencoder. 607-612 - Cheng Yan, Guihua Duan, Fang-Xiang Wu:
EMDS: predicting essential miRNAs based on deep learning and sequences. 613-618 - Lifeng Yan, Zekun Yin, Hao Zhang, Zhan Zhao, Mingkai Wang, André Müller, Robin Kobus, Yanjie Wei, Beifang Niu, Bertil Schmidt, Weiguo Liu:
RabbitQCPlus: More Efficient Quality Control for Sequencing Data. 619-626 - Wenjie Yao, Weizhong Zhao, Xingpeng Jiang, Xianjun Shen, Tingting He:
MPGNN-DSA: A Meta-path-based Graph Neural Network for drug-side effect association prediction. 627-632 - Shengwei Ye, Weizhong Zhao, Xianjun Shen, Xingpeng Jiang, Tingting He:
A Novel Drug Repositioning Model Based on Heterogeneous Graph Convolutional Network via Multi-task Learning. 633-638 - Jun Yu, Benjamin Zalatan, Yong Chen, Li Shen, Lifang He:
Tensor-Based Multi-Modal Multi-Target Regression for Alzheimer's Disease Prediction. 639-646 - Xueling Yuan, Weizhong Zhao, Xianjun Shen, Xingpeng Jiang, Tingting He:
Prediction of Drug-Drug Interactions Based on Meta-path-based Fusion Mechanism in Heterogeneous Information Network. 647-652 - Xiaoyu Zhang, Yike Guo:
OmiTrans: Generative Adversarial Networks Based Omics-to-omics Translation Framework. 653-659 - Jin Zhang, Muheng Shang, Qiang Xie, Minjianan Zhang, Duo Xi, Lei Guo, Junwei Han, Lei Du:
A Sparse Multi-task Contrastive and Discriminative Learning Method with Feature Selection for Brain Imaging Genetics. 660-665 - Yan Zhang, Jiru Li, Zhihao Yang, Hongfei Lin, Jian Wang:
Location-Guided Token Pair Tagger for Joint Biomedical Entity and Relation Extraction. 666-671 - Leilei Zhang, Junfei Liu:
Intent-aware Prompt Learning for Medical Question Summarization. 672-679