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ORCIDBriefings in Bioinformatics, Volume 26
Volume 26, Number 1, 2024
- Yiwen Yang
, Chengming Zhang, Zhaonan Liu, Kazuyuki Aihara, Chuanchao Zhang, Luonan Chen, Wu Wei:
MCGAE: unraveling tumor invasion through integrated multimodal spatial transcriptomics. - Tianjiao Zhang, Xiang Zhang, Zhenao Wu, Jixiang Ren, Zhongqian Zhao, Hongfei Zhang, Guohua Wang, Tao Wang:
VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell-cell communication network. - Xiaoyi Li, Kangli Zhu, Ying Zhen:
A versatile pipeline to identify convergently lost ancestral conserved fragments associated with convergent evolution of vocal learning. - Zhen Wang, Yizhen Feng, Qingwen Tian, Ziqi Liu, Pengju Yan, Xiaolin Li:
RNADiffFold: generative RNA secondary structure prediction using discrete diffusion models. - James Strudwick, Laura-Jayne Gardiner, Kate Denning-James, Niina Haiminen, Ashley Evans, Jennifer Kelly, Matthew Madgwick, Filippo Utro, Ed Seabolt, Christopher Gibson, Bharat Bedi, Daniel Clayton, Ciaron Howell, Laxmi Parida, Anna Paola Carrieri:
AutoXAI4Omics: an automated explainable AI tool for omics and tabular data. - Xin Ma, Lijing Lin, Qian Zhao, Mudassar Iqbal:
TriTan: an efficient triple nonnegative matrix factorization method for integrative analysis of single-cell multiomics data. - Anna Postovskaya, Koen Vercauteren, Pieter Meysman, Kris Laukens:
tcrBLOSUM: an amino acid substitution matrix for sensitive alignment of distant epitope-specific TCRs. - Jiachen Chen, Joanne M. Murabito, Kathryn L. Lunetta:
ONDSA: a testing framework based on Gaussian graphical models for differential and similarity analysis of multiple omics networks. - Yinhu Li, Guangze Pan, Shuai Wang, Zhengtu Li, Ru Yang, Yiqi Jiang, Yu Chen, Shuaicheng Li, Bairong Shen:
Comprehensive human respiratory genome catalogue underlies the high resolution and precision of the respiratory microbiome. - Saurav Chandra Das, Wahia Tasnim, Humayan Kabir Rana, Uzzal Kumar Acharjee, Md. Manowarul Islam, Rabea Khatun:
Comprehensive bioinformatics and machine learning analyses for breast cancer staging using TCGA dataset. - Alfred Ultsch, Jörn Lötsch:
Augmenting small biomedical datasets using generative AI methods based on self-organizing neural networks. - Yuqi Miao, Huang Xu, Shuang Wang:
PartIES: a disease subtyping framework with Partition-level Integration using diffusion-Enhanced Similarities from multi-omics Data. - Elisabet Munté, Carla Roca, Jesús del Valle, Lidia Feliubadaló, Marta Pineda, Bernat Gel, Elisabeth Castellanos, Barbara Rivera, David Cordero, Víctor Moreno, Conxi Lázaro, José Marcos Moreno-Cabrera:
Detection of germline CNVs from gene panel data: benchmarking the state of the art. - Yuhan Wang, Zhikang Wang, Xuan Yu, Xiaoyu Wang, Jiangning Song, Dong-Jun Yu, Fang Ge:
MORE: a multi-omics data-driven hypergraph integration network for biomedical data classification and biomarker identification. - Hai Cui, Meiyu Duan, Haijia Bi, Xiaobo Li, Xiaodi Hou, Yi-Jia Zhang:
Heterogeneous graph contrastive learning with gradient balance for drug repositioning. - Sara Cuvertino, Terence Garner, Evgenii Martirosian, Bridgious Walusimbi, Susan J. Kimber, Siddharth Banka, Adam Stevens:
Higher order interaction analysis quantifies coordination in the epigenome revealing novel biological relationships in Kabuki syndrome. - Marin Volaric, Nevenka Mestrovic, Evelin Despot-Slade:
SatXplor - a comprehensive pipeline for satellite DNA analyses in complex genome assemblies. - Correction to: HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction.
- Junning Feng, Yong Liang, Tianwei Yu:
ADM: adaptive graph diffusion for meta-dimension reduction. - Yuejun Tan, Linhai Xie, Hong Yang, Qingyuan Zhang, Jinyuan Luo, Yanchun Zhang:
BioDSNN: a dual-stream neural network with hybrid biological knowledge integration for multi-gene perturbation response prediction. - Yuxiao Wei, Qi Zhang, Liwei Liu:
The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs. - Long Xu, Qiang Yang, Weihe Dong, Xiaokun Li, Kuanquan Wang, Suyu Dong, Xianyu Zhang, Tiansong Yang, Gongning Luo, Xingyu Liao, Xin Gao, Guohua Wang:
Meta learning for mutant HLA class I epitope immunogenicity prediction to accelerate cancer clinical immunotherapy. - Leandro Murgas, Gianluca Pollastri, Erick Riquelme, Mauricio Sáez, Alberto J. M. Martin:
Understanding relationships between epigenetic marks and their application to robust assignment of chromatin states. - Ivan Ferrari, Federica De Grossi, Giancarlo Lai, Stefania Oliveto, Giorgia Deroma, Stefano Biffo, Nicola Manfrini:
CancerHubs: a systematic data mining and elaboration approach for identifying novel cancer-related protein interaction hubs. - Xiaolong Zhang, Xianchao Ji, Lingxiang Wang, Lianjiang Chi, Chengtao Li, Shaoqing Wen, Hua Chen:
STRsensor: a computationally efficient method for STR allele-typing from massively parallel sequencing data. - Expression of Concern: Bioinformatics in Russia: history and present-day landscape.
- Yunlong Wang, Siyuan Kong, Cong Zhou, Yanfang Wang, Yubo Zhang, Yaping Fang, Guoliang Li:
A review of deep learning models for the prediction of chromatin interactions with DNA and epigenomic profiles. - Shuailin Xue, Fangfang Zhu, Jinyu Chen, Wenwen Min:
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN. - Tong Lu, Wei Guo, Wei Guo, Wangyang Meng, Tianyi Han, Zizhen Guo, Chengqiang Li, Shugeng Gao, Youqiong Ye, Hecheng Li:
A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity. - Hao Yuan, Parker Hicks, Mansooreh Ahmadian, Kayla A. Johnson, Lydia Valtadoros, Arjun Krishnan:
Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata. - Zhenxian Zheng, Yingxuan Ren, Lei Chen, Angel On Ki Wong, Shumin Li, Xian Yu, Tak Wah Lam, Ruibang Luo:
Repun: an accurate small variant representation unification method for multiple sequencing platforms. - Tianyu Liu, Wenxin Long, Zhiyuan Cao, Yuge Wang, Chuan Hua He, Le Zhang, Stephen M. Strittmatter, Hongyu Zhao:
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis. - Fatma S. Ahmed, Saleh K. H. Aly, Xiangrong Liu:
NABP-BERT: NANOBODY®-antigen binding prediction based on bidirectional encoder representations from transformers (BERT) architecture. - Yong Liu, Le Zhong, Bin Yan, Zhuobin Chen, Yanjia Yu, Dan Yu, Jing Qin, Junwen Wang:
A self-attention-driven deep learning framework for inference of transcriptional gene regulatory networks. - Lu-Bin Cui, Guiliang Guo, Michael K. Ng, Quan Zou, Yushan Qiu:
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering. - Zheyu Ding, Rong Wei, Jianing Xia, Yonghao Mu, Jiahuan Wang, Yingying Lin:
Exploring the potential of large language model-based chatbots in challenges of ribosome profiling data analysis: a review. - Mengya Liu, Zhan-Li Sun, Zhigang Zeng, Kin-Man Lam:
Multi-kernel feature extraction with dynamic fusion and downsampled residual feature embedding for predicting rice RNA N6-methyladenine sites. - Aimin Xie, Hao Wang, Jiaxu Zhao, Zhaoyang Wang, Jinyuan Xu, Yan Xu:
scPAS: single-cell phenotype-associated subpopulation identifier. - Xizi Luo, Amadeus Song Yi Chi, Andre Huikai Lin, Tze Jet Ong, Limsoon Wong, Chowdhury Rafeed Rahman:
Benchmarking recent computational tools for DNA-binding protein identification. - Ornit Nahman, Timothy J. Few-Cooper, Shai S. Shen-Orr:
Cell-specific priors rescue differential gene expression in spatial spot-based technologies. - Xinglong Wang, Kangjie Xu, Lingling Ma, Ruoxi Sun, Kun Wang, Ruiyan Wang, Junli Zhang, Wenwen Tao, Kai Linghu, Shuyao Yu, Jingwen Zhou:
Diffusion model assisted designing self-assembling collagen mimetic peptides as biocompatible materials. - Bo Wang, Yahui Long, Yuting Bai, Jiawei Luo, Chee Keong Kwoh:
STCGAN: a novel cycle-consistent generative adversarial network for spatial transcriptomics cellular deconvolution. - Boya Ji, Xiaoqi Wang, Xiang Wang, Liwen Xu, Shaoliang Peng:
scDCA: deciphering the dominant cell communication assembly of downstream functional events from single-cell RNA-seq data. - Correction to: Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach.
- Konstantina Tzavella, Adrián Díaz, Catharina Olsen, Wim F. Vranken:
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep. - Cathal Ormond, Niamh M. Ryan, Mathieu Cap, William Byerley, Aiden P. Corvin, Elizabeth A. Heron:
BICEP: Bayesian inference for rare genomic variant causality evaluation in pedigrees. - Tianjiao Zhang, Hao Sun, Zhenao Wu, Zhongqian Zhao, Xingjie Zhao, Hongfei Zhang, Bo Gao, Guohua Wang:
GAADE: identification spatially variable genes based on adaptive graph attention network. - Shan Tharanga, Eyyüb Selim Ünlü, Yongli Hu, Muhammad Farhan Sjaugi, Muhammet A Çelik, Hilal Hekimoglu, Olivo Miotto, Muhammed Miran Öncel, Asif M. Khan:
DiMA: sequence diversity dynamics analyser for viruses. - Shyamsundar Ravishankar, Vilma Perez, Roberta Davidson, Xavier Roca-Rada, Divon Lan, Yassine Souilmi, Bastien Llamas:
Filtering out the noise: metagenomic classifiers optimize ancient DNA mapping. - Cui-Xiang Lin, Hong-Dong Li, Jianxin Wang:
LIMO-GCN: a linear model-integrated graph convolutional network for predicting Alzheimer disease genes. - Yan-Yu Li, Fengcui Qian, Guo-Rui Zhang, Xue-Cang Li, Li-Wei Zhou, Zheng-Min Yu, Wei Liu, Qiu-Yu Wang, Chunquan Li:
FunlncModel: integrating multi-omic features from upstream and downstream regulatory networks into a machine learning framework to identify functional lncRNAs. - Xueshi Yu, Renmin Han, Haitao Jiao, Wenjia Meng:
Few-shot classification of Cryo-ET subvolumes with deep Brownian distance covariance. - Xiaolong Wu, Lehan Zhang, Xiaochu Tong, Yitian Wang, Zimei Zhang, Xiangtai Kong, Shengkun Ni, Xiaomin Luo, Mingyue Zheng, Yun Tang, Xutong Li:
miCGR: interpretable deep neural network for predicting both site-level and gene-level functional targets of microRNA. - Shuhe Liu, Zhen Wei, Daniel F. Carr, John Moraros:
Deciphering the genetic interplay between depression and dysmenorrhea: a Mendelian randomization study. - Peng Liu, Yuchen Pan, Hung-Ching Chang, Wenjia Wang, Yusi Fang, Xiangning Xue, Jian Zou, Jessica M. Toothaker, Oluwabunmi Olaloye, Eduardo Gonzalez Santiago, Black McCourt, Vanessa Mitsialis, Pietro Presicce, Suhas G. Kallapur, Scott B. Snapper, Jia-Jun Liu, George C. Tseng, Liza Konnikova, Silvia Liu:
Comprehensive evaluation and practical guideline of gating methods for high-dimensional cytometry data: manual gating, unsupervised clustering, and auto-gating. - Yixuan Wang, Yanfang Guan, Xin Lai, Yuqian Liu, Zhili Chang, Xiaonan Wang, Quan Wang, Jingjing Liu, Jian Zhao, Shuanying Yang, Jiayin Wang, Xiaofeng Song:
THOR: a TMB heterogeneity-adaptive optimization model predicts immunotherapy response using clonal genomic features in group-structured data. - Junhang Cao, Jun Zhang, Qiyuan Yu, Junkai Ji, Jianqiang Li, Shan He, Zexuan Zhu:
TG-CDDPM: text-guided antimicrobial peptides generation based on conditional denoising diffusion probabilistic model. - Yunjian Chang, Ligang Wu:
CapHLA: a comprehensive tool to predict peptide presentation and binding to HLA class I and class II. - Pawel Dudzic, Bartosz Janusz, Tadeusz Satlawa, Dawid Chomicz, Tomasz Gawlowski, Rafal Grabowski, Przemek Józwiak, Mateusz Tarkowski, Maciej Mycielski, Sonia Wróbel, Konrad Krawczyk:
RIOT - Rapid Immunoglobulin Overview Tool - annotation of nucleotide and amino acid immunoglobulin sequences using an open germline database. - Junlei Liao, Hongyang Yi, Hao Wang, Sumei Yang, Duanmei Jiang, Xin Huang, Mingxia Zhang, Jiayin Shen, Hongzhou Lu, Yuanling Niu:
CDCM: a correlation-dependent connectivity map approach to rapidly screen drugs during outbreaks of infectious diseases. - Sergio Llaneza-Lago, William D. Fraser, Darrell Green:
Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes. - Dries Heylen, Murih Pusparum, Jurgis Kuliesius, Jim Wilson, Young-Chan Park, Jacek Jamiolkowski, Valentino D'onofrio, Dirk Valkenborg, Jan Aerts, Gökhan Ertaylan, Jef Hooyberghs:
Synthetic plasma pool cohort correction for affinity-based proteomics datasets allows multiple study comparison. - Yi Zhang, Yin Wang, Xinyuan Liu, Xi Feng:
CPARI: a novel approach combining cell partitioning with absolute and relative imputation to address dropout in single-cell RNA-seq data. - Nana Jin, Chuanchuan Nan, Wanyang Li, Peijing Lin, Yu Xin, Jun Wang, Yuelong Chen, Yuanhao Wang, Kaijiang Yu, Changsong Wang, Chunbo Chen, Qingshan Geng, Lixin Cheng:
PAGE-based transfer learning from single-cell to bulk sequencing enhances model generalization for sepsis diagnosis. - Qianwen Luo, Shanshan Zhang, Hamza Butt, Yin Chen, Hongmei Jiang, Lingling An:
PhyImpute and UniFracImpute: two imputation approaches incorporating phylogeny information for microbial count data. - Ankang Wei, Zhen Xiao, Lingling Fu, Weizhong Zhao, Xingpeng Jiang:
Predicting phage-host interactions via feature augmentation and regional graph convolution. - Chi Zhang, Yiran Cheng, Kaiwen Feng, Fa Zhang, Renmin Han, Jieqing Feng:
UPicker: a semi-supervised particle picking transformer method for cryo-EM micrographs. - Willem Stock, Coralie Rousseau, Glen Dierickx, Sofie D'hondt, Luz Amadei Martínez, Simon M. Dittami, Luna M. van der Loos, Olivier De Clerck:
Breaking free from references: a consensus-based approach for community profiling with long amplicon nanopore data. - Junwei Luo, Jiaojiao Wang, Jingjing Wei, Chaokun Yan, Huimin Luo:
DeepHapNet: a haplotype assembly method based on RetNet and deep spectral clustering. - Runqing Wang, Qiguo Dai, Xiaodong Duan, Quan Zou:
stHGC: a self-supervised graph representation learning for spatial domain recognition with hybrid graph and spatial regularization. - Lin Yuan, Shengguo Sun, Yufeng Jiang, Qinhu Zhang, Lan Ye, Chun-Hou Zheng, De-Shuang Huang:
scRGCL: a cell type annotation method for single-cell RNA-seq data using residual graph convolutional neural network with contrastive learning. - Jiaqi Wang, Ronggang Xi, Yi Wang, Huiyuan Gao, Ming Gao, Xiaozhe Zhang, Lihua Zhang, Yukui Zhang:
Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach.
Volume 26, Number 2, 2025
- Hailin Chen, Kuan Chen:
Ensemble learning based on matrix completion improves microbe-disease association prediction. - Minfang Song, Shuai Ma, Gong Wang, Yukun Wang, Zhenzhen Yang, Bin Xie, Tongkun Guo, Xingxu Huang, Liye Zhang:
Benchmarking copy number aberrations inference tools using single-cell multi-omics datasets. - Pengfei Zhu, Han Shu, Yongtian Wang, Xiaofeng Wang, Yuan Zhao, Jialu Hu, Jiajie Peng, Xuequn Shang, Zhen Tian, Jing Chen, Tao Wang:
MAEST: accurately spatial domain detection in spatial transcriptomics with graph masked autoencoder. - Mira Koul, Shalini Kaushik, Kavya Singh, Deepak Sharma:
VITALdb: to select the best viroinformatics tools for a desired virus or application. - Jing Zou, Wenyi Zhang, Jun Hu, Xiaogen Zhou, Biao Zhang:
DockEM: an enhanced method for atomic-scale protein-ligand docking refinement leveraging low-to-medium resolution cryo-EM density maps. - Yijun Mao, Jiale Wu, Jian Weng, Ming Li, Yunyan Xiong, Wanrong Gu, Rongjin Jiang, Rui Pang, Xudong Lin, Deyu Tang:
Inter-view contrastive learning and miRNA fusion for lncRNA-protein interaction prediction in heterogeneous graphs. - Ruijun Mao, Li Wan, Minghao Zhou, Dongxi Li:
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis. - Jinmiao Song, Yatong Hao, Shuang Zhao, Peng Zhang, Qilin Feng, Qiguo Dai, Xiaodong Duan:
Dual-stream cross-modal fusion alignment network for survival analysis. - Yongfei Hu, Xinyu Li, Ying Yi, Yan Huang, Guangyu Wang, Dong Wang:
Deep learning-driven survival prediction in pan-cancer studies by integrating multimodal histology-genomic data. - Carolina Monzó, Maider Aguerralde-Martin, Carlos Martínez-Mira, Angeles Arzalluz-Luque, Ana Conesa, Sonia Tarazona:
MOSim: bulk and single-cell multilayer regulatory network simulator. - Bo Li, Yongkang Zhao, Jing Hu, Shihua Zhang, Xiaolong Zhang:
scSAMAC: saliency-adjusted masking induced attention contrastive learning for single-cell clustering. - Jilong Bian, Hao Lu, Limin Wei, Yang Li, Guohua Wang:
Relational similarity-based graph contrastive learning for DTI prediction. - Kasmika Borah, Himanish Shekhar Das, Ram Kaji Budhathoki, Khursheed Aurangzeb, Saurav Mallik:
DOMSCNet: a deep learning model for the classification of stomach cancer using multi-layer omics data. - Wenhan Guo, Yuan Gao, Dan Du, Jason E. Sanchez, Yupeng Li, Weihong Qiu, Lin Li:
Elucidating the interactions between Kinesin-5/BimC and the microtubule: insights from TIRF microscopy and molecular dynamics simulations. - Nathaniel S. O'Connell, Byron C. Jaeger, Garrett S. Bullock, Jaime Lynn Speiser:
A comparison of random forest variable selection methods for regression modeling of continuous outcomes. - Maria Llambrich, Frans M. van der Kloet, Lluc Sementé, Anaïs Rodrigues, Saer Samanipour, Pierre-Hugues Stefanuto, Johan A. Westerhuis, Raquel Cumeras, Jesús Brezmes:
GcDUO: an open-source software for GC × GC-MS data analysis. - Sizhe Qiu, Bozhen Hu, Jing Zhao, Weiren Xu, Aidong Yang:
Seq2Topt: a sequence-based deep learning predictor of enzyme optimal temperature. - Gefei Zhao, Binbin Lai:
SC-VAR: a computational tool for interpreting polygenic disease risks using single-cell epigenomic data. - Xuexin Chen, Ruichu Cai, Zhengting Huang, Zijian Li, Jie Zheng, Min Wu:
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers. - Adriano Fonzino, Pietro Luca Mazzacuva, Adam Handen, Domenico Alessandro Silvestris, Annette Arnold, Riccardo Pecori, Graziano Pesole, Ernesto Picardi:
REDInet: a temporal convolutional network-based classifier for A-to-I RNA editing detection harnessing million known events. - Jean-Pierre Borg, Jacques Colinge, Patrice Ravel:
Testing and overcoming the limitations of modular response analysis. - Meng Yuan, Seppe Goovaerts, Myoung K. Lee, Jay Devine, Stephen Richmond, Susan Walsh, Mark D. Shriver, John R. Shaffer, Mary L. Marazita, Hilde Peeters, Seth M. Weinberg, Peter Claes:
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants. - Liang Chen, Madison Dautle, Ruoying Gao, Shaoqiang Zhang, Yong Chen:
Inferring gene regulatory networks from time-series scRNA-seq data via GRANGER causal recurrent autoencoders. - Yichong Li, Xiaoyong Pan, Hongbin Shen, Yang Yang:
DRAG: design RNAs as hierarchical graphs with reinforcement learning. - Saleh Sereshki, Stefano Lonardi:
Predicting differentially methylated cytosines in TET and DNMT3 knockout mutants via a large language model. - Duc Hai Nguyen, Woong-Ki Kim:
Disrupted microbial cross-feeding and altered L-phenylalanine consumption in people living with HIV. - Yuguang Li, Zhen Tian, Xiaofei Nan, Shoutao Zhang, Qinglei Zhou, Shuai Lu:
HSSPPI: hierarchical and spatial-sequential modeling for PPIs prediction. - Mingfei Han, Xiaoqing Chen, Xiao Li, Jie Ma, Tao Chen, Chunyuan Yang, Juan Wang, Yingxing Li, Wenting Guo, Yunping Zhu:
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data. - Correction to: STMGraph: spatial-context-aware of transcriptomes via a dual-remasked dynamic graph attention model.
- Yixuan Jin, Juanjuan Huang, Xu Sun, Yabo Fang, Jiageng Wu, Jianshi Du, Jiwei Jia, Guoqing Wang:
GiGs: graph-based integrated Gaussian kernel similarity for virus-drug association prediction. - Annette Spooner, Mohammad Karimi Moridani, Barbra Toplis, Jason Behary, Azadeh Safarchi, Salim Maher, Fatemeh Vafaee, Amany Zekry, Arcot Sowmya:
Benchmarking ensemble machine learning algorithms for multi-class, multi-omics data integration in clinical outcome prediction. - Xiaoyan Zhou, Luca Parisi, Wentao Huang, Yihan Zhang, Xiaoqun Huang, Mansour Youseffi, Farideh Javid, Renfei Ma:
A novel integrative multimodal classifier to enhance the diagnosis of Parkinson's disease. - Shuang Ge, Shuqing Sun, Huan Xu, Qiang Cheng, Zhixiang Ren:
Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective. - Yahao Wu, Jing Liu, Yanni Xiao, Shuqin Zhang, Limin Li:
CoupleVAE: coupled variational autoencoders for predicting perturbational single-cell RNA sequencing data. - Oleksandr Narykov, Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Fangfang Xia, Maulik Shukla, Priyanka Vasanthakumari, James H. Doroshow, Rick L. Stevens:
Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting. - Wei Xu, Gang Luo, Weiyu Meng, Xiaobing Zhai, Keli Zheng, Ji Wu, Yanrong Li, Abao Xing, Junrong Li, Zhifan Li, Ke Zheng, Kefeng Li:
MRAgent: an LLM-based automated agent for causal knowledge discovery in disease via Mendelian randomization. - Nicolaas F. V. Burger, Vittorio F. Nicolis, Anna-Maria Botha:
Evaluating long-read assemblers to assemble several aphididae genomes. - Abir Omran, Alexander Amberg, Gerhard F. Ecker:
Exploring diverse approaches for predicting interferon-gamma release: utilizing MHC class II and peptide sequences. - Laszlo Dobson, Gábor E. Tusnády, Peter Tompa:
Regularly updated benchmark sets for statistically correct evaluations of AlphaFold applications. - Shifu Luo, Hui Peng, Ying Shi, Jiaxin Cai, Songming Zhang, Ningyi Shao, Jinyan Li:
Integration of proteomics profiling data to facilitate discovery of cancer neoantigens: a survey. - Qi Dong, Yingying Guo, Chen Lv, Lingxue Ren, Bo Chen, Yan Wang, Yang Liu, Mingyue Liu, Kaidong Liu, Nan Zhang, Linzhu Wang, Shaocong Sang, Xin Li, Yang Hui, Haihai Liang, Yunyan Gu:
Unveiling a novel cancer hallmark by evaluation of neural infiltration in cancer. - Himansu Kumar, Abayomi Adegunlehin, Zikang Chen, Pora Kim:
FusionPub, a therapeutic landscape of human fusion genes. - Qiufeng Chen, Lijun Quan, Lexin Cao, Bei Zhang, Zhijun Zhang, Liangchen Peng, Junkai Wang, Yelu Jiang, Liangpeng Nie, Geng Li, Tingfang Wu, Qiang Lyu:
DS-MVP: identifying disease-specific pathogenicity of missense variants by pre-training representation. - Jair Herazo-Álvarez, Marco Mora, Sara Cuadros-Orellana, Karina Vilches-Ponce, Ruber Hernández-García:
A review of neural networks for metagenomic binning. - Xiaoyan Wang, Junwei Luo, Lili Wu, Huimin Luo, Fei Guo:
deepTAD: an approach for identifying topologically associated domains based on convolutional neural network and transformer model. - Emily C. Hector, Daiwei Zhang, Leqi Tian, Junning Feng, Xianyong Yin, Tianyi Xu, Markku Laakso, Yun Bai, Jiashun Xiao, Jian Kang, Tianwei Yu:
Dissecting genetic regulation of metabolic coordination. - Shrabanti Chowdhury, Sammy Ferri-Borgogno, Peng Yang, Wenyi Wang, Jie Peng, Samuel C. Mok, Pei Wang:
Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer. - Alessandra Aldieri, Thiranja Prasad Babarenda Gamage, Antonino Amedeo La Mattina, Axel Loewe, Francesco Pappalardo, Marco Viceconti:
Consensus statement on the credibility assessment of machine learning predictors. - Elise Jorge, Sylvain Foissac, Pierre Neuvial, Matthias Zytnicki, Nathalie Vialaneix:
A comprehensive review and benchmark of differential analysis tools for Hi-C data. - Hanwen Zhang, Deng Xiong, Xianggen Liu, Jiancheng Lv:
MolEM: a unified generative framework for molecular graphs and sequential orders. - Oleksandr Cherednichenko, Maria S. Poptsova:
Kolmogorov-Arnold networks for genomic tasks. - Zhen Gao, Yansen Su, Jin Tang, Huaiwan Jin, Yun Ding, Rui-Fen Cao, Pi-Jing Wei, Chun-Hou Zheng:
AttentionGRN: a functional and directed graph transformer for gene regulatory network reconstruction from scRNA-seq data. - De-Min Liang, Pu-Feng Du:
scMUG: deep clustering analysis of single-cell RNA-seq data on multiple gene functional modules. - Yunhui Qi, Xinyi Wang, Li-Xuan Qin:
Optimizing sample size for supervised machine learning with bulk transcriptomic sequencing: a learning curve approach. - Haolong Zeng, Chaoyi Yin, Chunyang Chai, Yuezhu Wang, Qi Dai, Huiyan Sun:
Cancer gene identification through integrating causal prompting large language model with omics data-driven causal inference. - Riikka Huusari, Tianduanyi Wang, Sándor Szedmák, Diogo Dias, Tero Aittokallio, Juho Rousu:
Scaling up drug combination surface prediction. - Qi Ge, Rui Qin, Shuang Liu, Quan Guo, Changcai Han, Weigang Chen:
Pragmatic soft-decision data readout of encoded large DNA. - Sijie Li, Heyang Hua, Shengquan Chen:
Graph neural networks for single-cell omics data: a review of approaches and applications. - Xusheng Ai, Melissa C. Smith, F. Alex Feltus:
GEMDiff: a diffusion workflow bridges between normal and tumor gene expression states: a breast cancer case study. - Bingqing Han, Yipeng Zhang, Longlong Li, Xinqi Gong, Kelin Xia:
TopoQA: a topological deep learning-based approach for protein complex structure interface quality assessment. - Jiashan Li, Xi Chen, He Huang, Mingliang Zeng, Jingcheng Yu, Xinqi Gong, Qiwei Ye:
$\mathcal{S}$ able: bridging the gap in protein structure understanding with an empowering and versatile pre-training paradigm. - Xuwen Wang, Zhili Chang, Yuqian Liu, Shenjie Wang, Xiaoyan Zhu, Yang Shao, Jiayin Wang:
EMcnv: enhancing CNV detection performance through ensemble strategies with heterogeneous meta-graph neural networks. - Peng Zhou, Zixiu Li, Feifan Liu, Euijin Kwon, Tien-Chan Hsieh, Shangyuan Ye, Shobha Vasudevan, Jung Ae Lee, Khanh-Van Tran, Chan Zhou:
BAMBI integrates biostatistical and artificial intelligence methods to improve RNA biomarker discovery. - Zhimin Li, Wenlan Chen, Hai Zhong, Cheng Liang:
PCLSurv: a prototypical contrastive learning-based multi-omics data integration model for cancer survival prediction. - Jie Ni, Bin Li, Shumei Miao, Xinting Zhang, Donghui Yan, Shengqi Jing, Shan Lu, Zhuoying Xie, Xin Zhang, Yun Liu:
MethPriorGCN: a deep learning tool for inferring DNA methylation prior knowledge and guiding personalized medicine.
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