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Bioinformatics 2024: all accepted papers

788 papers · page 1 of 8 · the most cited first · ← Bioinformatics 2024

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  1. ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries ↗Kyle Swanson, Parker Walther, Jeremy Leitz et al.372 citations
  2. RCSB protein Data Bank: exploring protein 3D similarities via comprehensive structural alignments ↗Sebastian Bittrich, Joan Segura, José M. Duarte et al.211 citations
  3. GeneGPT: augmenting large language models with domain tools for improved access to biomedical informationQiao Jin, Yifan Yang, Qingyu Chen et al.174 citations · our summary
  4. Biomedical knowledge graph-optimized prompt generation for large language models ↗Karthik Soman, Peter W. Rose, John H Morris et al.136 citations
  5. Improving medical reasoning through retrieval and self-reflection with retrieval-augmented large language modelsMinbyul Jeong, Jiwoong Sohn, Mujeen Sung et al.131 citations · our summary
  6. BCFtools/liftover: an accurate and comprehensive tool to convert genetic variants across genome assemblies ↗Giulio Genovese, Nicole B. Rockweiler, Bryan R. Gorman et al.120 citations
  7. Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice ↗Bjarne Daenekas, Eilís Pérez, Fabio Boniolo et al.120 citations
  8. Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES): a method for populating knowledge bases using zero-shot learning ↗John Harry Caufield, Harshad Hegde, Vincent Emonet et al.120 citations
  9. DAVID Ortholog: an integrative tool to enhance functional analysis through orthologs ↗Brad T. Sherman, Ganesh Prabhakar Panzade, Tomozumi Imamichi et al.110 citations
  10. KRAGEN: a knowledge graph-enhanced RAG framework for biomedical problem solving using large language models ↗Nicholas Matsumoto, Jay Moran, Hyun‐Jun Choi et al.108 citations
  11. selscan 2.0: scanning for sweeps in unphased data ↗Zachary A. Szpiech106 citations
  12. Parsnp 2.0: scalable core-genome alignment for massive microbial datasets ↗Bryce L. Kille, Michael Nute, Victor Huang et al.105 citations
  13. Advancing entity recognition in biomedicine via instruction tuning of large language models ↗Vipina K. Keloth, Yan Hu, Qianqian Xie et al.104 citations
  14. Bin2cell reconstructs cells from high resolution Visium HD data ↗Krzysztof Polański, Raquel Bartolomé-Casado, Ioannis Sarropoulos et al.100 citations
  15. DockQ v2: improved automatic quality measure for protein multimers, nucleic acids, and small molecules ↗Claudio Mirabello, Björn Wallner95 citations
  16. DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm ↗Matee Ullah, Shahid Akbar, Ali Raza et al.74 citations
  17. Predicting the subcellular location of prokaryotic proteins with DeepLocPro ↗Jaime Moreno, Henrik Nielsen, Ole Winther et al.74 citations
  18. POCP-nf: an automatic Nextflow pipeline for calculating the percentage of conserved proteins in bacterial taxonomy ↗Martin Hölzer72 citations
  19. Addressing the antibody germline bias and its effect on language models for improved antibody design ↗Tobias Hegelund Olsen, Iain H. Moal, Charlotte Mary Deane67 citations
  20. lefser: implementation of metagenomic biomarker discovery tool, LEfSe, in R ↗Asya Khleborodova, Samuel David Gamboa-Tuz, Marcel Ramos et al.66 citations
  21. TemStaPro: protein thermostability prediction using sequence representations from protein language models ↗Ieva Pudžiuvelytė, Kliment Olechnovič, Eglė Godliauskaitė et al.65 citations
  22. DTI-LM: language model powered drug–target interaction prediction ↗Khandakar Tanvir Ahmed, Md. Istiaq Ansari, Wei Zhang62 citations
  23. ModDotPlot—rapid and interactive visualization of tandem repeats ↗Alexander P. Sweeten, Michael C. Schatz, Adam M. Phillippy62 citations
  24. iNGNN-DTI: prediction of drug–target interaction with interpretable nested graph neural network and pretrained molecule models ↗Yan Sun, Yan Yi Li, Carson Kai-Sang Leung et al.59 citations
  25. RT-Transformer: retention time prediction for metabolite annotation to assist in metabolite identification ↗Jun Xue, Bingyi Wang, Hongchao Ji et al.56 citations
  26. Bioframe: operations on genomic intervals in Pandas dataframes ↗Open2C, Nezar A. Abdennur, Geoffrey Fudenberg et al.53 citations
  27. Chainsaw: protein domain segmentation with fully convolutional neural networks ↗Jude Wells, Alex Hawkins‐Hooker, Nicola Bordin et al.53 citations
  28. scMAE: a masked autoencoder for single-cell RNA-seq clustering ↗Zhaoyu Fang, Ruiqing Zheng, Min Li50 citations
  29. HGTDR: Advancing drug repurposing with heterogeneous graph transformers ↗Ali Gharizadeh, Karim Abbasi, Amin Ghareyazi et al.49 citations
  30. Effect of tokenization on transformers for biological sequences ↗Edo Dotan, Gal Jaschek, Tal Pupko et al.48 citations
  31. Pathformer: a biological pathway informed transformer for disease diagnosis and prognosis using multi-omics data ↗Xiao Fan Liu, Yuhuan Tao, Zilin Cai et al.48 citations
  32. wgd v2: a suite of tools to uncover and date ancient polyploidy and whole-genome duplication ↗Hengchi Chen, Arthur Zwaenepoel, Yves Van de Peer47 citations
  33. Drug–target interaction predictions with multi-view similarity network fusion strategy and deep interactive attention mechanism ↗Wei Song, Lewen Xu, Chenguang Han et al.46 citations
  34. scDiffusion: conditional generation of high-quality single-cell data using diffusion model ↗Erpai Luo, Minsheng Hao, Lei Wei et al.46 citations
  35. Revisiting drug–protein interaction prediction: a novel global–local perspective ↗Zhecheng Zhou, Qingquan Liao, Jinhang Wei et al.44 citations
  36. grenedalf: population genetic statistics for the next generation of pool sequencing ↗Lucas Czech, Jeffrey P. Spence, Moisés Expósito‐Alonso44 citations
  37. Tiberius: end-to-end deep learning with an HMM for gene prediction ↗Lars Gabriel, Felix Becker, Katharina J. Hoff et al.43 citations
  38. HiPhase: jointly phasing small, structural, and tandem repeat variants from HiFi sequencing ↗James Holt, Christopher T. Saunders, William J. Rowell et al.41 citations
  39. PMIpred: a physics-informed web server for quantitative protein–membrane interaction prediction ↗Niek van Hilten, Nino Verwei, Jeroen Methorst et al.41 citations
  40. Panacus: fast and exact pangenome growth and core size estimation ↗Luca Parmigiani, Erik P. Garrison, Jens Stoye et al.41 citations
  41. CryoTransformer: a transformer model for picking protein particles from cryo-EM micrographs ↗Ashwin Dhakal, Rajan Gyawali, Liguo Wang et al.40 citations
  42. Contrastive pre-training and 3D convolution neural network for RNA and small molecule binding affinity prediction ↗Saisai Sun, Lin Gao39 citations
  43. Molecular property prediction based on graph structure learning ↗Bangyi Zhao, Weixia Xu, Jihong Guan et al.39 citations
  44. Towards the accurate modelling of antibody−antigen complexes from sequence using machine learning and information-driven docking ↗Marco Giulini, Constantin Schneider, Daniel Cutting et al.39 citations
  45. PocketDTA: an advanced multimodal architecture for enhanced prediction of drug−target affinity from 3D structural data of target binding pockets ↗Long Zhao, Hongmei Wang, Shaoping Shi38 citations
  46. The GenoPred pipeline: a comprehensive and scalable pipeline for polygenic scoring ↗Oliver Pain, Ammar Al‐Chalabi, Cathryn M. Lewis38 citations
  47. ABodyBuilder3: improved and scalable antibody structure predictions ↗Henry Kenlay, Frédéric A. Dreyer, Daniel Cutting et al.35 citations
  48. VarChat: the generative AI assistant for the interpretation of human genomic variations ↗Federica De Paoli, Silvia Berardelli, Ivan Limongelli et al.35 citations
  49. MOIRE: a software package for the estimation of allele frequencies and effective multiplicity of infection from polyallelic data ↗Maxwell Murphy, Bryan Greenhouse34 citations
  50. MetaCerberus: distributed highly parallelized HMM-based processing for robust functional annotation across the tree of life ↗Jose L. Figueroa, Eliza Dhungel, Madeline Bellanger et al.34 citations
  51. CodonBERT: a BERT-based architecture tailored for codon optimization using the cross-attention mechanism ↗Zilin Ren, Lili Jiang, Yaxin Di et al.33 citations
  52. Expert-guided protein language models enable accurate and blazingly fast fitness prediction ↗Céline Marquet, Julius Schlensok, Marina Abakarova et al.33 citations
  53. Exploring gene content with pangene graphs ↗Heng Li, Maximillian G. Marin, Maha Reda Farhat33 citations
  54. Representations of lipid nanoparticles using large language models for transfection efficiency prediction ↗Saeed Moayedpour, Jonathan Broadbent, Saleh Riahi et al.33 citations
  55. Accurate and transferable drug–target interaction prediction with DrugLAMP ↗Zhengchao Luo, Wei Wu, Qichen Sun et al.32 citations
  56. AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors ↗Raúl Fernández-Díaz, Rodrigo Cossio-Pérez, Clement Agoni et al.32 citations
  57. Flexiplex: a versatile demultiplexer and search tool for omics data ↗Oliver Cheng, Min Hao Ling, Changqing Wang et al.32 citations
  58. Surface-based multimodal protein–ligand binding affinity prediction ↗Shiyu Xu, Lian Shen, Menglong Zhang et al.32 citations
  59. Unravelling reference bias in ancient DNA datasets ↗Stephanie Dolenz, Tom van der Valk, Chenyu Jin et al.32 citations
  60. InstaPrism: an R package for fast implementation of BayesPrism ↗Mengying Hu, Maria D. Chikina31 citations
  61. Phenotype prediction from single-cell RNA-seq data using attention-based neural networks ↗Yuzhen Mao, Yen‐Yi Lin, Nelson K.Y. Wong et al.31 citations
  62. ViraLM: empowering virus discovery through the genome foundation model ↗Cheng Peng, Jiayu Shang, Jiaojiao Guan et al.31 citations
  63. BioCoder: a benchmark for bioinformatics code generation with large language models ↗Xiangru Tang, Bill Qian, Rick Gao et al.30 citations
  64. Integrated convolution and self-attention for improving peptide toxicity prediction ↗Shihu Jiao, Xiucai Ye, Tetsuya Sakurai et al.30 citations
  65. NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection ↗Chenglin Yin, Ruheng Wang, Jianbo Qiao et al.30 citations
  66. OligoFormer: an accurate and robust prediction method for siRNA design ↗Yilan Bai, Haochen Zhong, Taiwei Wang et al.30 citations
  67. ScType enables fast and accurate cell type identification from spatial transcriptomics data ↗Kristen Michelle Nader, Mısra Tascı, Aleksandr Ianevski et al.30 citations
  68. pyaging : a Python-based compendium of GPU-optimized aging clocks ↗Lucas Paulo de Lima Camillo30 citations
  69. AleRax: a tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss ↗Benoit Morel, Tom A. Williams, Alexandros Stamatakis et al.29 citations
  70. HyperTMO: a trusted multi-omics integration framework based on hypergraph convolutional network for patient classification ↗Haohua Wang, Kai Yan Lin, Qiang Zhang et al.29 citations
  71. M-Ionic: prediction of metal-ion-binding sites from sequence using residue embeddings ↗Aditi Shenoy, Yogesh Kalakoti, Durai Sundar et al.29 citations
  72. STRING-ing together protein complexes: corpus and methods for extracting physical protein interactions from the biomedical literature ↗Farrokh Mehryary, Katerina C. Nastou, Tomoko Ohta et al.29 citations
  73. CryptoBench: cryptic protein–ligand binding sites dataset and benchmark ↗Vít Škrhák, Marián Novotný, Christos P Feidakis et al.28 citations
  74. GCI: a continuity inspector for complete genome assembly ↗Quanyu Chen, Chentao Yang, Guojie Zhang et al.28 citations
  75. Interpretable deep learning in single-cell omics ↗Manoj M Wagle, Siqu Long, Carissa Chen et al.28 citations
  76. PGAT-ABPp: harnessing protein language models and graph attention networks for antibacterial peptide identification with remarkable accuracy ↗Yuelei Hao, Xuyang Liu, Haohao Fu et al.28 citations
  77. Rapid generation of high-quality structure figures for publication with PyMOL-PUB ↗Yuting Chen, Haoling Zhang, Wen Wang et al.28 citations
  78. RiboDiffusion: tertiary structure-based RNA inverse folding with generative diffusion models ↗Han Huang, Ziqian Lin, Dongchen He et al.28 citations
  79. TA-RNN: an attention-based time-aware recurrent neural network architecture for electronic health records ↗Mohammad Al Olaimat, Serdar Bozdag, Alzheimer’s Disease Neuroimaging Initiative28 citations
  80. scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism ↗Qun Jiang, Shengquan Chen, Xiaoyang Chen et al.28 citations
  81. DeepRSMA: a cross-fusion-based deep learning method for RNA–small molecule binding affinity prediction ↗Zhijian Huang, Yucheng Wang, Song Chen et al.27 citations
  82. FMCA-DTI: a fragment-oriented method based on a multihead cross attention mechanism to improve drug–target interaction prediction ↗Qi Zhang, Le Zuo, Ying Ren et al.27 citations
  83. PractiCPP: a deep learning approach tailored for extremely imbalanced datasets in cell-penetrating peptide prediction ↗Kexin Shi, Yuanpeng Xiong, Yu Wang et al.27 citations
  84. SeedMatchR: identify off-target effects mediated by siRNA seed regions in RNA-seq experiments ↗Tareian A. Cazares, Richard E. Higgs, Jibo Wang et al.27 citations
  85. DEAttentionDTA: protein–ligand binding affinity prediction based on dynamic embedding and self-attention ↗Xiying Chen, Jinsha Huang, Tianqiao Shen et al.26 citations
  86. MINDG: a drug–target interaction prediction method based on an integrated learning algorithm ↗Hailong Yang, Yue Chen, Yun Zuo et al.26 citations
  87. Seq-InSite: sequence supersedes structure for protein interaction site prediction ↗SeyedMohsen Hosseini, Geoffrey Brian Golding, Lucian Ilie26 citations
  88. Attention-based approach to predict drug–target interactions across seven target superfamilies ↗Aron Schulman, Juho Rousu, Tero A. Aittokallio et al.25 citations
  89. Clustering single-cell multi-omics data via graph regularized multi-view ensemble learning ↗Fuqun Chen, Guanhua Zou, Yongxian Wu et al.25 citations
  90. DeepCRISTL: deep transfer learning to predict CRISPR/Cas9 on-target editing efficiency in specific cellular contexts ↗Shai Elkayam, Ido Tziony, Yaron Orenstein25 citations
  91. SharePro: an accurate and efficient genetic colocalization method accounting for multiple causal signals ↗Wenmin Zhang, Tianyuan Lu, ROBERT M. SLADEK et al.25 citations
  92. scNODE : generative model for temporal single cell transcriptomic data prediction ↗Jiaqi Zhang, Erica Larschan, Jeremy Bigness et al.25 citations
  93. A physics-informed neural SDE network for learning cellular dynamics from time-series scRNA-seq data ↗Qi Jiang, Lin Wan24 citations
  94. BWT construction and search at the terabase scale ↗Heng Li24 citations
  95. FuncFetch: an LLM-assisted workflow enables mining thousands of enzyme–substrate interactions from published manuscripts ↗Nathaniel S. S. Smith, Xinyu Yuan, Chesney Melissinos et al.24 citations
  96. GPro: generative AI-empowered toolkit for promoter design ↗Haochen Wang, Qixiu Du, Ye Wang et al.24 citations
  97. LMCrot: an enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language model ↗Pawel Pratyush, Soufia Bahmani, Suresh Pokharel et al.24 citations
  98. Prediction of antibiotic resistance mechanisms using a protein language model ↗Kanami Yagimoto, Shion Hosoda, Miwa Sato et al.24 citations
  99. ReMASTER: improved phylodynamic simulation for BEAST 2.7 ↗Timothy G. Vaughan24 citations
  100. Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations ↗Kangcheng Hou, Stephanie M. Gogarten, Joohyun Kim et al.23 citations

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