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ORCIDBriefings in Bioinformatics, Volume 27
Volume 27, Number 1, 2026
- Yu Zhang
, Ming Li, David M. Haas, C. Noel Bairey Merz, Tsegaselassie Workalemahu, Kelli Ryckman, Janet M. Catov, Lisa D. Levine, Alexa Freedman, George R. Saade, Jiaqi Hu, Hongyu Zhao, Xihao Li, Nianjun Liu, Qi Yan:
A novel two-sample Mendelian randomization framework integrating common and rare variants: application to assess the effect of HDL-C on preeclampsia risk. - Wenli Zhai, Lingyun Sun, Wenwei Fang, Yidan Dong, Chunxiao Cheng, Yuanjiao Liu, Yuan Zhou, Jiadong Ji, Lang Wu, An Pan, Eric R. Gamazon, Xiong-Fei Pan, Dan Zhou:
Cross-ancestry information transfer framework improves protein abundance prediction and protein-trait association identification. - Lena Maria Hackl, Fabian Neuhaus, Sabine Ameling, Uwe Völker, Jan Baumbach, Olga Tsoy:
Detection of alternative splicing: deep sequencing or deep learning? - Yonglin Peng, Xinhua Liu, Jun Wu, Sang Lin, Shengxuan Zhan, Hua Li, Ju Wang, Xiaodong Zhao:
EpiXFormer: a cross-attention neural network for predicting cell type-specific transcription factor binding sites. - Minrui Xu, Manman Lu, Peng Liu, Siwen Zhang, Lanming Chen, Qi Liu, Yong Lin, Lu Xie:
ProTCR: a protein language model-driven framework for decoding TCR-antigen recognition toward precision immunotherapies. - Yosra Berrouayel, Luis del Peso:
Enhancing TFEA.ChIP with ENCODE regulatory maps for generalizable transcription factor enrichment. - Chenjie Feng, Xiaowen Sun, Xintao Song, Lei Bao, Weikang Gong, Renmin Han:
DeepRMSF: a deep learning-based automated approach for predicting atomic-level flexibility in RNA structure. - Ruhai Chen, Jiekai Chen, Lingling Shi, Jiangping He:
iceDP: identifying inter-chromatin engagement via density peaks clustering algorithm. - Youshu Cheng, Chen Lin, Hongyu Li, Ke Xu, Hongyu Zhao:
UBD: incorporating uncertainty in cell type proportion estimates from bulk samples to infer cell-type-specific profiles. - Dong Chen, Yuquan Wang, Dapeng Shi, Yunlong Cao, Yue-Qing Hu:
MACFIV: a novel framework for nonlinear causal inference in the body mass index-hypertension relationship with many weak and pleiotropic genetic instruments. - Wonkyeong Jang, Woong-Hee Shin:
CoBRA: compound binding site prediction using RNA language model. - Zhen Tian, Xiaojiao Wei, Zhengzheng Lou, Zhixia Teng, Shouli Fu:
Adaptive multi-view information bottleneck for multi-omics data clustering. - Alexander Partin, Priyanka Vasanthakumari, Oleksandr Narykov, Andreas Wilke, Natasha Koussa, Sara E. Jones, Yitan Zhu, Jamie C. Overbeek, Rajeev Jain, Gayara Demini Fernando, Cesar Sanchez-Villalobos, Cristina Garcia-Cardona, Jamaludin Mohd-Yusof, Nicholas Chia, Justin M. Wozniak, Souparno Ghosh, Ranadip Pal, Thomas S. Brettin, M. Ryan Weil, Rick L. Stevens:
Benchmarking community drug response prediction models: datasets, models, tools, and metrics for cross-dataset generalization analysis. - Sang-Pil Cho, Young-Rae Cho:
GRAFT: a graph-aware fusion transformer for cancer driver gene prediction. - Bingyan Wang, Heng Hu, Runtian Gao, Guohua Wang, Tao Jiang:
GFSeeker: a splicing-graph-based approach for accurate gene fusion detection from long-read RNA sequencing data. - Can Shi, Yumei Li, Jing Guo, Qiuling Chen, Tingting Cao, Sha Liao, Ao Chen, Mei Li, Ying Zhang:
CSRefiner: a lightweight framework for fine-tuning cell segmentation models with small datasets. - Jiayi Li, Shenglun Chen, Zhixing Wu, Haozhe Wang, Rong Xia, Jia Meng, Yuxin Zhang:
CircRM: profiling circular RNA modifications from nanopore direct RNA sequencing. - Bosheng Song, Jiayi Zhang, Ying Liu, Yuansheng Liu, Jing Jiang, Sisi Yuan, Xia Zhen, Yiping Liu:
A systematic review of molecular representation learning foundation models. - Inas Bosch, Barbara Gravel, Alexandre Renaux, Ann Nowé, Maris Laan, Tom Lenaerts:
Benchmarking knowledge graph embedding models for the prediction of oligogenic combinations. - Xunuo Zhu, Wenyi Zhao, Siqi Wang, Jingwen Yang, Jingqi Zhou, Binbin Zhou, Ji Cao, Bo Yang, Zhan Zhou, Xun Gu:
Identification of cancer mini-drivers by deciphering selective landscape in the cancer genome.
Volume 27, Number 2, 2026
- Zhihao Wang, Sheng Wang, Jingjing Guo, Yuguang Mu, Xiangdong Liu, Liangzhen Zheng, Weifeng Li:
Could statistical potential models achieve comparable or better performance than deep learning models? - Vincenzo Laveglia, Cosimo Ciofalo, Enrico Morelli, Claudia Andreini, Antonio Rosato:
Master of Metals2: a graph neural network based architecture for the prediction of zinc binding sites in protein structures. - Jing Wang, Junfeng Xia, Yansen Su, Chun-Hou Zheng:
scSCCNIA: similarity matrix based contrastive clustering with neighbor information aggregation for single-cell RNA sequencing data. - Publisher's Note: Addendum to Volume 26, Issue Supplement 1, December 2025, International Conference on Genome Informatics ISCB-Asia 2025 Abstract Book.
- Sandeep Acharya, Vaha Akbary Moghaddam, Wooseok J. Jung, Yu S. Kang, Shu Liao, Michael A. Province, Michael R. Brent:
Finding Significant Hits in Networks: a network-based tool for analyzing gene-level P -values to identify significant genes missed by standard methods. - Lotta Eriksson, Eszter Lakatos:
Sensitive detection of copy number alterations in low-pass liquid biopsy sequencing data. - Cheng Zhong, Siqi Jiang, Zhi Wei:
Integrating feature selection with unsupervised deep embedding for clustering single-cell RNA-seq data. - Jingzhan Lu, Johan Hilge Thygesen, Robin N. Beaumont, Michael N. Weedon, Harry D. Green:
Impact of control selection strategies on GWAS results: a study of prostate cancer in the UK Biobank. - Ashitha Washington, Ravindra Kumar:
Machine Learning Driven Discovery of Ribosomal Biomarkers in PCOS. 2- - Shuang-Hao Yang, Hua He, Shuyu Hou, Tuanfeng Yang, Zehao Yin, Hong-Yu Zhang, Weiyue Gu:
ML-ExonCNV: a robust XGBoost multi-expert ensemble framework for rare exon CNV detection in whole-exome sequencing data. - Mingqing Liu, Jinhui Xu, Ji Liu:
A progressive fine-tuning framework with dynamic parameter selection for low-resource peptide-GPCR interaction prediction. - Yang Deng, Jinhao Que, Guangfu Xue, Yideng Cai, Wenyi Yang, Yilin Wang, Yi Hui, Zuxiang Wang, Yi Lin, Wenyang Zhou, Zhaochun Xu, Qinghua Jiang, Haoxiu Sun:
AI-driven computational methods and benchmarking for T-cell antigen identification. - He Wang, Yikun Zhang, Jie Chen, Jian Zhan, Yaoqi Zhou:
Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning. - Qiong Chen, Boliang Zhang, Chen Peng, Jiajun Huang, Zhen Liu, Xiaotao Shen, Chao Jiang:
Kun-peng enables scalable and accurate pan-domain metagenomic classification. - Daohong Gong, Xiaowei Xie, Jianxin Tang, Shiliang Li, Honglin Li:
Transformer-based multidimensional feature fusion for accurate prediction of lipid nanoparticles transfection efficiency. - Lingyu Li, Wai-Ki Ching, Zhi-Ping Liu:
Prognostic biomarker discovery via a connected network-constrained Cox proportional hazards model. 1- - Sunil Nagpal:
Supervisory signals are intriguingly high in even simple features for predicting anticancer effect of antibody drug conjugates. - Paramita Roy, Dibakar Roy, Sudipto Bhattacharjee, Abhirupa Ghosh, Sudipto Saha:
MDPD reveals specific microbial signatures in human pulmonary diseases. - Huasen Jiang, Xiaoyu Huang, Xiangpeng Bi, Wenjian Ma, Haibo Ni, Zhiqiang Wei, Pin Sun, Henggui Zhang, Shugang Zhang:
Artificial intelligence-enabled multi-scale virtual cell: perspective, challenges, and opportunities. - Yiyi Yu, Jiyuan Yang, Ping-An He, Xiaoqi Zheng:
Castl: robust identification of spatially variable genes in spatial transcriptomics via an ensemble-based framework. - Yongli Peng, Yujing Deng, Menghan Liu, Zhiyuan Liu, Ya-Hui Li, Xiang-Yu Zhao, Dong Xing, Jinzhu Jia, Hao Ge:
scDIAGRAM: detecting chromatin compartments from individual single-cell Hi-C matrix without imputation or reference features. - Lihui Jin, Zhenyuan Han, Rebecca Hannah, Hongyu Shao, Junxin Huang, Shiying Wang, Weibin Zhang, Jiang Lin, Kun Sun, Yu Yu:
Computational identification of lineage-committed precursors in mammalian organogenesis reveals a novel hematopoietic enhancer regulating Bhlhe41 expression. - Bui Tien Thanh, Yoichi Kurumida, Kaito Kobayashi, Michiaki Hamada, Tomoshi Kameda:
Differentiation of RNA-protein docking structures through molecular dynamics simulation and machine learning methods. - M. D. Youshuf Khan Rakib, Muhammad Habibulla Alamin, Jiamu Li, Sheikh Sohan Mamun, Kaleb Amsalu Gobena, Shengbing Ren:
KANPM-DTA: improving drug-target affinity prediction with Kolmogorov-Arnold networks and pretrained models. - Sudipto Baul, Naima Ahmed Fahmi, Guangyu Wang, Hao Zheng, Ahmed Louri, Jeongsik Yong, Wei Zhang:
EpGAT: integrating epigenetics and 3D genome structure to predict alternative splicing and polyadenylation. - Chenyu Ren, Daihai He, Jian Huang:
De novo functional protein sequence generation: overcoming data scarcity through regeneration and large language models. - Alexa H. Beachum, Xue Xiao, Yuansheng Zhou, Qiwei Li, Guanghua Xiao, Lin Xu:
Advances in predicting omics profiles from imaging data. - Chuyun Zhang, Kei Hang Katie Chan:
An integrative multi-omics framework for decoding microglial ecosystems in Alzheimer's disease. 3- - Juntao Deng, Miao Gu, Pengyan Zhang, Tao Liu, Guansong Hu, Mingyu Dong, Yabin Zhang, Yizhen Song, Yunfan Zhang, Min Liu, Junzhang Tian, Weibin Cheng:
MutPPI+: a multimodal framework for predicting mutation effects on protein-protein interactions via mutation-path-based data augmentation. - Syed Mohammed Khalid, Tom Wölker, Leidy-Alejandra G. Molano, Simon Graf, Andreas Keller:
Benchmarking large language models for pathogen-disease classification in post-acute infection syndromes. - Shuo Zhang, Jike Qi, Yuchen Jiang, Hua Lin, Xinyi Wang, Ting Wang, Hongyan Cao, Ping Zeng:
An integrative association analysis for complex diseases in underrepresented groups by leveraging the trans-ethnic genetic similarity. - Mawada Elmagboul Abdalla Abakar, Mehad Almagboul Abdalla Abaker, Marco Antoniotti, Alex Graudenzi:
Phylogenetic analysis of TET2 gene variants in Pakistani acute myeloid Leukemia patients. 4- - Yizhou Zeng, Lei Wang, Xueming Liu:
BioMNEDR: mechanism-guided network embedding for drug repurposing. - Peter T. Nguyen, Maria Zhivagui:
SigRescueR : a pan-system framework for noise correction and mutational signature identification across sequencing platforms. - Wasif Jalal, Mubasshira Musarrat, Md. Abul Hassan Samee, M. Sohel Rahman:
ORANGE: a machine learning approach for modeling tissue-specific aging from transcriptomic data. - Junlin Xu, Cheng Guo, Yajie Meng, Shuting Jin, Changcheng Lu, Zilong Zhang, Feifei Cui, Xiangzheng Fu, Quan Zou, Tian Tian, Xiangxiang Zeng:
A deep adversarial network model for multi-task analysis of single-cell omics data. - Chun Shang, Kevin C. Chan, Ruhong Zhou:
Decoding TCR recognition via geometric deep learning of immunological fingerprints.
Volume 27, Number 3, 2026
- Shuilin Liao, Haoxiang Yang, Shuting Xiao, Zhiwen Li, Qi Zhu, Le Li, Shanghui Lu, Yong Liang, Ming Dong:
DADA-EV: domain-adaptive diffusion autoencoder for estimating tissue- and cell-type-specific origin in extracellular vesicle transcriptomes. - Zechen Zhang, Hui Yang, Meilin Zhu, Ran Guo, Fuzhao Chen, Hui Dong, Yuehua Cui, Haitao Yang:
Nonlinear kernel-based high-dimensional inference for set-based genetic association studies. - Yi Hao, Heyun Sun, Zixu Ran, Xudong Guo, Ming Liu, Yue Bi, Jose Polo, Ning Liu, Fuyi Li:
Graph-based RNA structural representation reveals determinants of subcellular localization. - Zhen Li, Xuejian Cui, Xiaoyang Chen, Zijing Gao, Yuyao Liu, Yan Pan, Shengquan Chen, Hairong Lv, Lei Zhai, Rui Jiang:
Cross-modality representation and multi-sample integration of spatially resolved omics data. - Kahn Rhrissorrakrai, Kathleen E. Hamilton, Prerana Bangalore Parthasarathy, Aldo Guzmán-Sáenz, Shreya Gupta, Tyler Alban, Filippo Utro, Laxmi Parida:
Quantum ensembling methods for healthcare and life science. - Panwen Wang, Yanxi Chen, Yong Liu, Li Liu, Ping Yang, Junwen Wang, Zhifu Sun:
ceQTL: a co-expression QTL model to detect a variant that affects transcription factor binding and its target regulation. - Yi Wang, Hongyu Li, Lun Li, Yongrong Cao, Zhijian Duan, Shuhui Song:
scHILL: deciphering individual-level immune cell heterogeneity with single-cell RNA sequencing data. - Jingzhan Lu, Johan Hilge Thygesen, Robin N. Beaumont, Michael N. Weedon, Harry D. Green:
Impact of control selection strategies on GWAS results: a study of prostate cancer in the UK biobank. - Akash Reddy Kothakapu, Sharanya Madugula, Saketh Bharadwaj Sharma Gandeed, Kavya Sri Sai Yadlapati, Sharanya Sury, Vani Kondaparthi:
SE(3)-PROTACs: Geometric deep learning for PROTAC degradation prediction. - Siguo Wang, Zhipeng Li, Hailin Feng, Zhen Cui, Zhen-Hao Guo, Qi Liao, Zuquan Hu, Wenjian Liu, Qinhu Zhang, De-Shuang Huang:
GraphLooper: predicting chromatin loops based on hierarchical multi-view graph pooling method. - Sizhe Qiu, Aidong Yang:
Response to "Addressing flaws in the Seq2Topt dataset for the prediction of enzyme optimal temperature". - Victor Epain, Aniket C. Mane, Cédric Chauve:
On using clustering statistics for assessing plasmid binning tools accuracy. - Yuhua Fan, Ilkka Launonen, Mikko J. Sillanpää, Patrik Waldmann:
Proximal regularization of deep residual neural networks applied to high-dimensional genomic data. - Zeming Tan, Jiahao Li, Enfeng Qi, Ting Yu:
The impact of transcriptome assembly algorithms on downstream quantification in RNA-seq data analysis. - Julie Cartier, Johanna Lagoas, Youmna Ayadi, Adeline Fermanian, Chloé-Agathe Azencott, Florian Massip:
Statistical knockoffs improve biomarker discovery from transcriptomic data. - Correction to: DANet: spatial gene expression prediction from H&E histology images through dynamic alignment.
- Duong Thanh Tran, Nhat Truong Pham, Gwang Lee, Shaherin Basith, Balachandran Manavalan:
CONTRA-IL6: an interpretable hybrid convolutional neural network and Transformer framework for accurate prediction of interleukin-6-inducing peptides using protein language models. - Sudipta Sardar, Supriya Dash, Puja Roychowdhury, Jaykishan Solanki, Purbita Sikdar, Jayaraman Thangappan, Somenath Dutta:
Artificial intelligence for antimicrobial resistance: advancing reproducibility, interpretability, and clinical deployment. - Shabir Hussain, Muhammad Ayoub, Fei Ye, Xiao Liu:
MLN2SVG: domain-aware spatially variable gene detection using contrastive variational autoencoder and multi-level neighbor search. - Athan Z. Li, Yuxuan Du, Yan Liu, Liang Chen, Ruishan Liu:
Benchmarking computational methods for multi-omics biomarker discovery in cancer. - Ronnie Y. Li, Chang Su, Zhaohui S. Qin:
A novel machine learning-based algorithm for eQTL identification reveals complex pleiotropic effects in the MHC region. - Shuyi Deng, Hui Song, Cai Li:
MuRaL-indel: a deep learning framework for building insertion and deletion mutation rate maps. - Zi-long Yuan, Bo Wang, Yu-lu Chen, Hao-qi Huang, Bin-hao Li, Ahmed Zahoor, Liping Ren, Mengze Du, Rui-qin Fang, Lin Ning:
Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective. - Yunju Song, Hwan Choi, Sunyong Yoo:
Carcinogenicity prediction via multi-task learning of cross-organ representations with attention mechanisms. - Xue Li, Suheng Qiao, Ziqi Li, Shihua Zhou, Jianmin Wang, Bin Wang, Tao Song, Ben Cao:
Predicting protein-protein interaction sites based on dynamic perception mechanism within a hierarchical E(n)-equivariant graph. - Genjin Lin, Shitao Li, Kian-Kai Cheng, Zhaodong Fei, Lingli Deng, Jiyang Dong, Daniel Raftery:
ssNetShift: single-sample metabolic network rewiring reveals hidden prognostic subtypes beyond clinical staging in gastric cancer. - Jianan Sui, Weirong Cui, Xiaojie Jin, Hongliang Duan, Jingjing Guo:
MIFNDRA: an innovative knowledge-enhanced multimodal fusion and graph learning framework for predicting drug resistance-related ncRNAs. - Zhentao Liu, Arun Das, Wen Meng, Yu-Chiao Chiu, Shou-Jiang Gao, Yufei Huang:
ST2HE: enhancing spatial transcriptomics interpretability via virtual staining for histological annotation. - Tianneng Zhu, Zhijun Tong, Mingzhe Suo, Mingzi Xu, Asad Ullah, Feng Lin, Honghe Zhang, Bingguang Xiao, Hai-Ming Xu:
QTLNetwork-MP: integrative mapping of additive, epistatic, and G × E effects for complex traits in multiparent advanced generation intercross populations. - Xu Chen, Luoyuan Guo, Yaosheng Chen, Delin Mo, Xiaohong Liu:
USADAE: a deep learning approach to disentangle hidden covariates in RNA-seq data. - Shiyan Nie, Xiangren Kong, Dong Li:
Strategies for constructing context-specific protein-protein interaction networks. - Jing Liu, Yahao Wu, Limin Li:
DiSCO: deconvoluting spatial transcriptomics via combinatorial optimization with a foundational diffusion model. - Jiani Zhao, Kha Tram, Hongbin Yan, Yifeng Li:
Reply to "Letter to the editor: methodological considerations in the benchmarking of AI-based protein-aptamer complex prediction". - Yi Wang, Zihang He, Yunjie Yan:
SPOmiAlign: a modality-agnostic computational framework for multimodal spatial omics alignment enabled by a feature matching foundation model. - Po-Chun Chiu, Chia-Yi Lee, Heng-Cheng Hsu, Yi-Jou Tai, Ying-Cheng Chiang, Tzu-Pin Lu:
Development of a novel multimodal deep learning approach to improve diagnostic precision in ovarian cancer. - Katyna Sada del Real, Vinay S. Swamy, Josefina Arcagni, Eric Wang, Raul Rabadan, Angel Rubio:
Foundation models and deep learning for cancer drug response prediction: a framework for data, metrics, and validation. - Clément Bézier, Jakez Rolland, Ronan Boutin, Valérie Devauchelle-Pensec, Nathan Foulquier:
GEDO: topology-based inference of gene module activity in Sjögren's disease. - Biplab Poudel, Rajan Gyawali, Ashwin Dhakal, Jianlin Cheng, Dong Xu:
CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs. - Yejin Kan, Gangman Yi:
ProtDML: label-aware representation learning for broad-spectrum protein function prediction. - Li Ying Khoo, Sarinder Kaur Dhillon:
Comparative review of artificial intelligence for transcriptomic biomarker discovery in coronavirus disease 2019 (COVID-19). - Yingyi Jiang, Lei Jia, Yuan Fei, Xiaoguang Li, Xiaoqi Zheng, Yufang Qin:
StackAge: an ensemble-based clock for precise quantification of biological age using multi-omics data. - Ying Wang, Yuhao Deng, Hang Li, Xinbao Yin, Yanru Zhang, Yurong Chen, Min Zhang, Xin Wang, Zhizhuo Cao, Shaojun Zhang:
Inferring tumor absolute copy number and clonal substructure from single-cell chromatin accessibility. - Haidar Jomaa, Rida Assaf:
Computational prediction of replication origins: a comparative review of methods, benchmarks, and trends from heuristics to deep learning. - Ruiying Cao, Penghua Zhou, Xin Chen:
Modeling DNA storage retrieval reliability via sequencing coverage depth. - Philip J. Law, Molly Went, Richard S. Houlston:
Response to 'Impact of control selection strategies on GWAS results: a study of prostate cancer in the UK Biobank'. - Jinjing Shi, Peng Du, Wenwu Zeng, Wenxuan Wang, Shaoliang Peng, Xuelong Li:
QSyncFold: quantum neural network for multidimensional sync-discovery in protein folding. - Francesco Branda, Mohamed Mustaf Ahmed, Massimo Ciccozzi, Pietro Hiram Guzzi, Fabio Scarpa:
The next paradigm in bioinformatics: a review of multi-agent systems and foundational models for end-to-end scientific discovery. - Xiaoyan Li, Zhen Peng, Yiran Zhao, Shuhan Wang, Xingpeng Zhou, Xiongjian Luo, Yansen Su, Chun-Hou Zheng, Junfeng Xia:
Pathogenicity prediction for noncanonical splice-altering variants based on multimodal feature fusion. - David Schaeper, Upol Chowdhury, Sarath Chandra Janga:
Current trends and challenges in deciphering single molecule resolution maps of single cell transcriptomes. - Ali Jahangiri-Sisakht, Leila Safari, Roghayyeh Alipanahi:
CRISPR-MBTF: a multi-branch transformer fusion framework for CRISPR-Cas9 off-target prediction. - Sumit Mukherjee, Rami Zakh, Alexander Churkin, Danny Barash:
RNA design: update on computational frameworks and programs for inverse RNA folding. - Jingyun Liu, Zhicheng Ji:
Lense: optimizing data preprocessing in single-cell omics using large language models. - Md Ishtyaq Mahmud, Tania Banerjee:
Artificial Intelligence in genomics: a comprehensive survey of methods, resources, challenges, and prospects. - Jiani Zhao, Kha Tram, Hongbin Yan, Yifeng Li:
Comprehensive evaluation of artificial intelligence-empowered approaches for protein-aptamer complex prediction. - Beilei Bian, Yue Cao, Jean Yee Hwa Yang:
Estimating tumour immune infiltration: methodological convergence across histology and spatial technologies. - Yipei Yu, Meihua Long, Jiali Song, Kai Cao, Meimei Luo, Wei Liu, Zhiwei Rong, Yan Hou:
GAMMI: graph-guided contrastive and adversarial integration of single-cell and spatial multi-omics data. - Elias Hossain, Niloofar Yousefi:
Computational paradigms for antimicrobial resistance prediction: integrating multi-omics, structural modeling, and foundation artificial intelligence systems. - Thomas Ferté, Laura Villain, Rodolphe Thiébaut, Boris P. Hejblum:
Gene set analysis for time-to-event outcome: comparison of a new approach based on the generalized Berk-Jones statistic with existing methods in presence of intra gene-set correlation. - Thenmalarchelvi Rathinavelan, Sruthi Sundaresan:
Untangling or further entangling? Theoretical expansion of the structural landscape of nucleic acid quadruplexes and modeling with 3D-NuS-Qplex. - Marco Teixeira, Colin J. Worby, Thomas Abeel, Ashlee M. Earl, Abigail L. Manson:
Response to 'On using clustering statistics for assessing plasmid binning tools accuracy'. - Xingyu Chen, Zihan Wang, Min Deng, Jianxiang Huang, Naishu Zhang, Zheng Wu, Zelin Yi, Sangyu Li, Jiayue Qiu, Kit-Leong Cheong, Xin Chen, Chen Huang:
MMP3C v2: a network-based framework decoding metabolic plasticity in rheumatoid arthritis, enabling accurate diagnosis and uncovering cell-type-specific metabolic rewiring. - Hongyan Cao, Zhaoyang Xu, Shilong Lin, Gang Du, Tong Wang, Juping Wang, Xiaoling Yang, Ruiling Fang, Yanhong Luo, Ping Zeng, Hongmei Yu, Yanbo Zhang, Yuehua Cui:
CEDR: robust consensus cancer subtyping with multi-omics data via ensemble dimensionality reduction. - Shaine Chenxin Bao, Kathleen I Pishas, Karla J. Cowley, Qiong-Yi Zhao, Emily C. A Goodall, Ian R. Henderson, Xin Liu, Evanny Marinovic, Mark S. Carey, Ian G. Campbell, Kaylene J. Simpson, Dane Cheasley, Dalia Mizikovsky, Nathan J. Palpant:
A scalable, multi-resolution consensus clustering approach for prioritizing robust signals from high-throughput screens. - Jingyuan Wang, Yifan Liu, Fu Liu, Tao Hou, Siming Chen, Shengxi Liu, Yun Liu:
DCVBin: a novel binning method for single-sample metagenomes based on DNA language model and variational autoencoder. - Noa Konforti, Tal Goldberg, Michal Danino-Levi, Yael Ilan, Shahar Alon:
ModelistsGCN: a multimodal graph convolutional network framework for single-cell spatial transcriptomic cell typing. - Jingkai Zhang, Si Hoi Kou, Jiulu Zhao, Xiaomin Li, Yongbing Zhao:
scMarkerGene: an interpretable neural network framework for cell-type-specific marker gene discovery. - Farbod Mahmoudinobar, Grace Meng, J. Wade Davis, Sandeep Kumar:
An intrinsic sequence-structural profile for mRNA-delivered therapeutic antibodies. - Yuqiao Gong, Xin Yuan, Zhangsheng Yu:
Empowering multifaceted analysis of spatial transcriptomics data with RGAST. - Weicai Long, Rong Zhou, Wenkang Wei, Xiaoai Zhang, Shanshan Wu, Kui Li, Yanlin Zhang, Zishuai Wang:
Porcine MutBERT: a family of lightweight genomic foundation models for functional element prediction in pigs. - Partha Pratim Ray:
When intelligence begins to act: a thoughtful appraisal of agentic AI in biomedicine. - Kai Wang, Jiajun Qu, Fei Liu, Xiaoli Luan, Jingwen Zhou:
Hypergraph learning with multi-dimensional metabolite feature extractions and static-dynamic attention mechanisms to fill missing reactions in metabolic networks. - Paul Aurelian Gagniuc, Elvira Gagniuc:
The sequence alignment problem: boundary conditions as the unifying principle. - Yuhan Jiang, Ju Guo, Yifan Wang, Run Guo, Yongjian Wei, Tianchun Li, Xuelin Wang, Ruiwen Xia, Wanyi Li, Yingxue Zou, Hongxi Yang:
From early-onset asthma to chronic obstructive pulmonary disease: potential mediating proteins and therapeutic targets. - Zhipeng Qian, Jiaqi Yin, Chunlong Zhang, Guohua Wang, Chunyu Wang, Yang Li, Yuming Zhao:
Identification and characterization of lncRNA-stemness-immune regulatory patterns. - Senxin Zhang, Yining Qin, Hanwen Zhu, Feilong Meng, Lei Jia, Xiaoqi Zheng:
Deep Prior Framework: integrating functional specificity with general plausibility for targeted protein evolution. - Justyna Król, Maria Bochenek, Sylwia Jopa, Krzysztof Kazimierczuk, Anna Gambin, Michal Startek:
WNetAlign: fast and accurate spectra alignment using truncated Wasserstein distance and network simplex. - Yuxi Liu, Zhenhao Zhang, Mufan Qiu, Song Wang, Flora D. Salim, Jun Shen, Tianlong Chen, Imran Razzak, Fuyi Li, Jiang Bian:
GatorSC: multi-scale cell and gene graphs with mixture-of-experts fusion for single-cell transcriptomics. - Bruno Florentino, Robson Parmezan Bonidia, André C. P. L. F. de Carvalho:
Accessibility in proteins and RNAs interactions prediction with machine learning: are we overlooking non-experts? - Jiadong Lu, Xinyuan Zhu, Xinting Hu, Cheng Zhang, Fuli Feng:
Benchmarking TCR-pMHC structure prediction: a unified evaluation and CDR3-based functional insights. - Maria N. Chasapi, Nicholas Kontis, Robert Lehmann, Ruqaiya Tasneem, Niketan S. Patel, Sumeer Ahmad Khan, Xabier Martinez de Morentin, Iro N. Chasapi, Eleni Aplakidou, Alexandros Galaras, Lila Aldakheel, Minjing Su, Fotis A. Baltoumas, Kasthuri Venkateswaran, Vincenzo Lagani, David Gomez-Cabrero, Jesper Tegnér, Georgios A. Pavlopoulos, Alexandre Soares Rosado:
Decoding extremophiles: insights from bioinformatics, machine learning, and data-driven approaches. - Abdulaziz Ascandari, Suleiman Aminu, Rachid Benhida, Rachid Daoud:
From association to causation: a decision-aware framework for reproducible biomarker discovery and precision intervention design in the human gut microbiome. - Chenkui Wang, Qianhui Jiang, Dan Yu, Jiahui Guan, Zimeng Chen, Xiaoling Lu, Bin Yan, Jing Qin, Yong Liu, Junwen Wang:
DeepPTMPred: a multi-modal deep learning framework for accurate prediction of protein post-translational modification sites. - Martin J. Bishop:
Twenty-five years of briefings in bioinformatics. - Peng Zhou:
Addressing flaws in the Seq2Topt dataset for the prediction of enzyme optimal temperature. - Shuhe Liu, Xichen Zhao, Zhen Wei, Daniel F. Carr, John Moraros:
Decoding causal m6A: a bioinformatics roadmap for psychiatric disorders. - Jingyu Hao, Jiandong Shi, Sheng Lian, Zhen Zhang, Yongyi Luo, Taobo Hu, Toyotaka Ishibashi, De-Peng Wang, Shu Wang, Xiaodan Fan, Weichuan Yu:
gSV: a general structural variant detector using the third-generation sequencing data. - Kuan-Ju Liao, Yuh-Ju Sun:
Shoebill: an interpretable AlphaFold2-informed predictor of protein crystallization propensity using XGBoost. - Jiangwei Huang, Zhihan Yang, Mou Yin, Chao Li, Jinmin Li, Yu Wang, Lu Huang, Miaomiao Li, Chengzhi Liang, Fei He, Rongcheng Han, Yuqiang Jiang:
CLCNet: a contrastive learning and chromosome-aware network for genomic prediction in plants. - Yexuan Mao, Lijun Quan, Xiangyu Chen, Siyuan Wang, Guozheng Zhang, Siqi Li, Yelu Jiang, Liangpeng Nie, Tingfang Wu, Lingkun Meng, Qiang Lyu:
Identifying batch-integrated domains from spatial transcriptomics via graph autoencoder with contrastive learning based on cross-modality and data augmentation. - Laura Balbi, Rita T. Sousa, Pedro Cotovio, Catia Pesquita:
The role of protein embeddings for protein-protein interaction prediction with graph neural networks. - Tianjiao Zhang, Long Wan, Hongfei Zhang, Zhongqian Zhao, Haijie Cui, Jianli Ma:
CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images. - Lucía Schmidt-Santiago, Alejandro Guerrero-López, Carlos Sevilla-Salcedo, David Rodríguez-Temporal, Belén Rodríguez-Sánchez, Vanessa Gómez-Verdejo:
A systematic review of machine learning on clinical MALDI-TOF MS. - Srinivas Kashyap Chilakamarri, Sneha Reddy Kasturi, Sai Pranav Reddy Yerrabandla, Sanjana Gogte, Vani Kondaparthi:
InversePep: Diffusion-driven structure-based inverse folding for functional peptides. - Bandhan Sarker, Tianjiao Zhou, Xiaoling Deng, Lei Zhang, Xianjia Zhao, Weijun Huang, Hongliang Yi, Hangjin Jiang, Chuan Xu:
APAdeg enhances differentially expressed gene inference by leveraging site-specific signals in APA-seq data. - Hasan Zulfiqar, Ramala Masood Ahmad, Hao Lin, Xiao-Long Yu:
ac4C modification sites prediction in human mRNA: a complete review. - Lipsa Priyadarsinee, Vyacheslav Kungurtsev, Vibhor Kumar, Bapi Chatterjee, Garikapati Narahari Sastry, Natarajan Arul Murugan:
Contemporary data-driven innovations in peptide-based therapeutic design. - Alexander Gavrilenko, Maria Sindeeva, Tatiana Shashkova:
Cytokine-driven immunogenicity prediction: integrating HLA binding and cytokine induction. - Hao Liu, Yi Shi, Feiyu Guo, Jinyi Wang, Jiaqian Li, Guangji Wang, De-Chuan Zhan, Haiping Hao, Guo Yu:
MAPLE: interpretable deep learning identifies selective antimicrobial peptides using joint evolutionary-physicochemical analysis. - Shi Qiu, Chunguo Wu, Yuxiang Ma, Songye Gao, Limin Wang, Yanchun Liang, Xiaohu Shi:
KSDiffusion: conditional diffusion for kinase-specific phosphorylation site prediction under data-limited and imbalanced regimes. - Haoran Liu, Yuanjie Zou, Zhi Wei:
Semi-supervised disentangled representation learning for single-cell RNA sequencing data. - Weiyue Ding, Yang Zhou, Quanhong Liu, Yiyuan Guo, Chiping Zhang, Shuilin Jin:
Accurate and efficient HiChIP interaction detection by modeling restriction enzyme cut site density as biological signal. - Mano Joseph Mathew, Joyal Mathew, Ripsy Merrin Chacko, Jagadeesh Bayry, Jean-François Zagury:
Decoding disease and therapy through multiomics integration and systems analysis. - Thanh Hoa Vo, Nguyen Quoc Khanh Le:
Toward trustworthy artificial intelligence in multi-omics: a review of reproducibility, stability, and interpretability. - Romina Norouzi, Karim Abbasi, Parvin Razzaghi, Sajjad Gharaghani:
MT-ConBiFormer-GPT: multi-target molecular generation for low-data drug discovery via a contrastive BiFormer-GPT architecture and curriculum learning with cross-domain generalization. - Sutapa Das, Shashank Rao Padubidri, Sreelakshmi K. V, Koushik S. Shetty, Rutuparna Jena, Himabindu K. R, Budheswar Dehury, Arun Prasad Pandurangan:
From mechanistic modeling to AI-driven design: computational strategies for targeting the γ-secretase complex. - Jinxiong Zhang, Hedong Xu, Chunyan Tang, Dandan Ni, Xuyang Shen:
MDCDR: predicting cancer drug response via multimodal feature fusion and feature disentanglement. - Jialu Liang, Yanfei Wang, Xiao Fan, Mingyi Xie, Qianqian Song:
VIRSE: a variational Bayesian framework for RNA structural ensemble inference. - Davin Lee, Gaeun Byeon, Seojin Chung, Dongmin Shin, Jongseo Park, Ingyeon Koh, Joon-Yong An:
AnnQ: reference-based quantification of cellular abnormality at single-cell resolution. - Junchao Zhu, Ruining Deng, Junlin Guo, Tianyuan Yao, Siqi Lu, Chongyu Qu, Juming Xiong, Yanfan Zhu, Zhengyi Lu, Yuechen Yang, Marilyn Lionts, Yucheng Tang, Daguang Xu, Yu Wang, Shilin Zhao, Haichun Yang, Yuankai Huo:
A comprehensive survey of computer vision methods for spatial transcriptomics. - Yanchao Han, Jianfeng Mei, Gaoshuai Li, Enkang Dai, Hanlei Lu, Chengyun Zhang, Yanlu Zhang, Chenshui Lin, Chuanlong Zeng, Hongliang Duan, Xudong Wang:
HighRes_Builder: improved access and modeling of noncanonical residues for protein structure prediction. - Dylan H. Ross, Raghav Jain, Hyeyoon Kim, Javier E. Flores, Soumaydeep Sarkar, Chaevien S. Clendinen, Jennifer E. Kyle, Tao Liu, Sara J. C. Gosline:
Assessing current capabilities for incorporating lipidomics in multiomics data integration. - Partha Pratim Ray:
Reflections on the use of LLMs for cell annotation. - Yinuo Sun, Xiaoyu Wang, Yuheng Jia, Seiya Imoto, Fuyi Li, Chen Li, Jiangning Song:
Comprehensive review and assessment of multi-species splicing variant prediction: task-specific deep learning models and genomic foundation models. - Qi Li, Cody Nichols, Robert S. Welner, Jake Y. Chen, Wei-Shinn Ku, Zongliang Yue:
GOLDEN fusion: a graph-oriented learning with domain-embedding network fusion for generating super gene sets in functional genomics. - Xinning Shan, Yingxin Lin, Hongyu Zhao:
A unified framework for selecting and evaluating cell-type-specific gene co-expressions in single-cell data. - Hao Dong, Guo-Zheng Rao, Hao-Yu Wang, Xin-Ran Wu, Tong Xian, Bo-Qiang Wang, Pu-Feng Du:
GraphChIAr: genome-wide super-resolution reconstruction of protein-mediated remote chromatin interactions by augmenting hi-C interaction maps with multiple ChIP-seq profiles. - Shicheng Zhang, Koichi Saeki, Hiroshi Haeno:
geneSCOPE: gene spatial co-occurrence of pairwise expression. - Kazim Okan Dolu:
Letter to the editor: methodological considerations in the benchmarking of AI-based protein-aptamer complex prediction. - Laiyi Fu, Wenkai Cui, Yifan Chen, Danyang Wu, Hequan Sun:
Biased multi-view contrastive learning with attentive masking for spatial transcriptomic analysis. - Jing Li, Leyi Wei, Henry H. Y. Tong, Quan Zou:
Quantum computing applications in drug discovery. - Yawei Niu, Yichu Chen, Wenji Ma:
PVAED: prior-guided variational autoencoders with diffusion denoising for interpretable single-cell representation learning. - Aleksandra Zielinska, Michal Fornalik, Mateusz Szczepaniak, Mariola Gimla, Anna Lemanska, Judyta Cielecka-Piontek, Eliana B. Souto:
Artificial intelligence in drug research and development: a review of methods and applications in drug repurposing. - Cyrille Mesue Njume, Irene Petracci, Sonia Bellini, Katarzyna Goljanek-Whysall, Leo R. Quinlan, Agnieszka Fiszer, Barbara Borroni, Roberta Ghidoni, Asli Kumbasar, Ali Cakmak:
When complexity does not pay: benchmarking deep learning and ensemble methods for biomarker discovery. - Dao Tran, Yen Thi-Hai Pham, Hung N. Luu, Juli Petereit, Manuel A Andrade-Rodriguez, Phi Bya, Tin Nguyen:
CSIE: cancer subtyping via inference and ensemble. - Farzaneh M. Parizi, Yannick J. M. Aarts, Nils Smit, A R. Dona Roran, Daniëlle Diepenbroek, Wieke A Krösschell, Levin Thijs, Joost Tepperik, Dario F. Marzella, Gayatri Ramakrishnan, Li C. Xue:
SwiftTCR: efficient computational docking protocol of TCRpMHC-I complexes using restricted rotation matrices. - Deniz Gurarslan, Oscar Camargo, Omer Zeyveli, Yasin Almalioglu, Yanjun Li, Mehmet Turan, Tamer Kahveci:
STORM: spatial transcriptomics optimization by resolution via matrix factorization. - Jin-Feng Wang, Qixiong Long, Deyu Tang, Jin Deng, Yong Liang:
scMVAF: a multi-view adaptive fusion clustering approach for single-cell RNA-sequencing data. - Lei Xian, Quan Zou, Ren Qi, Mengting Niu, Yansu Wang:
MuFGPS: enhancing liquid-liquid phase separation protein prediction through multi-level features and ensemble learning. - Yiwei Fu, Jiaxiao Chen, Haoyu Lin, Zhonghui Gu, Qingqing Long, Hui Wan, Xiao Luo, Minghua Deng:
Out-of-distribution generalization enhances protein function annotation for low-homology sequences. - Peggy Berlin, Amin Mirzaei, Felix Steinbeck, Martin Becker, Brigitte Müller-Hilke, Wendy Bergmann-Ewert, Daniel Dubinski, Thomas M. Freiman, Daniel Strüder, Theresa Momper, Annabell Wolff, Philipp Kaps, Julia Henne, Clemens Schafmayer, Michael Linnebacher, Charlotte Wagner, Karen Rischmüller, Martin Philipp, Georg Lamprecht, Paul Meissner, Karoline Schulz, Christian Junghanss, Bernd Kreikemeyer, Sonja Oehmcke-Hecht, Claudia Maletzki:
Machine learning-guided multimodal profiling defines perturbed immune states at the time of cancer diagnosis.
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