---
title: "Bioinformatics 2024 — all accepted papers, page 2"
description: "All 788 papers of Bioinformatics 2024 · page 2 of 8, the most cited first; those with our summary link to it."
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---
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# Bioinformatics 2024: all accepted papers

788 papers · page 2 of 8 · the most cited first · [← Bioinformatics 2024](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/)

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101. **[MARS: a motif-based autoregressive model for retrosynthesis prediction ↗](https://doi.org/10.1093/bioinformatics/btae115)**Jiahan Liu, Chaochao Yan, Yang Yu et al.*23 citations*
102. **[Microbial interactions from a new perspective: reinforcement learning reveals new insights into microbiome evolution ↗](https://doi.org/10.1093/bioinformatics/btae003)**Parsa Ghadermazi, Siu Hung Joshua Chan*23 citations*
103. **[MolLM : a unified language model for integrating biomedical text with 2D and 3D molecular representations ↗](https://doi.org/10.1093/bioinformatics/btae260)**Xiangru Tang, Xiangru Tang, Jeffrey Too Chuan Tan et al.*23 citations*
104. **[PHIStruct: improving phage–host interaction prediction at low sequence similarity settings using structure-aware protein embeddings ↗](https://doi.org/10.1093/bioinformatics/btaf016)**Mark Edward M. Gonzales, Jennifer C. Ureta, Anish Man Singh Shrestha*23 citations*
105. **[Publication-ready single nucleotide polymorphism visualization with snipit ↗](https://doi.org/10.1093/bioinformatics/btae510)**Aine Niamh O’Toole, Ammar Aziz, Daniel M. Maloney*23 citations*
106. **[Sigmoni: classification of nanopore signal with a compressed pangenome index ↗](https://doi.org/10.1093/bioinformatics/btae213)**Vikram S. Shivakumar, Omar Y. Ahmed, Sam Kovaka et al.*23 citations*
107. **[YACHT : an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample ↗](https://doi.org/10.1093/bioinformatics/btae047)**David Koslicki, Stephen White, Chunyu Ma et al.*23 citations*
108. **[Benchmarking of AlphaFold2 accuracy self-estimates as indicators of empirical model quality and ranking: a comparison with independent model quality assessment programmes ↗](https://doi.org/10.1093/bioinformatics/btae491)**Nicholas S. Edmunds, Ahmet G Genc, Liam James McGuffin*22 citations*
109. **[GenoFig: a user-friendly application for the visualization and comparison of genomic regions ↗](https://doi.org/10.1093/bioinformatics/btae372)**Maxime Branger, Sébastien O Leclercq*22 citations*
110. **[NFTest: automated testing of Nextflow pipelines ↗](https://doi.org/10.1093/bioinformatics/btae081)**Yash Patel, Chenghao Zhu, Takafumi N. Yamaguchi et al.*22 citations*
111. **[NeoaPred: a deep-learning framework for predicting immunogenic neoantigen based on surface and structural features of peptide–human leukocyte antigen complexes ↗](https://doi.org/10.1093/bioinformatics/btae547)**Dawei Jiang, Binbin Xi, W.C. Tan et al.*22 citations*
112. **[methscore: a comprehensive R function for DNA methylation-based health predictors ↗](https://doi.org/10.1093/bioinformatics/btae302)**Zongli Xu, Liang Niu, Jacob K. Kresovich et al.*22 citations*
113. **[Causal enhanced drug–target interaction prediction based on graph generation and multi-source information fusion ↗](https://doi.org/10.1093/bioinformatics/btae570)**Guanyu Qiao, Guohua Wang, Yang Li*21 citations*
114. **[DDAffinity: predicting the changes in binding affinity of multiple point mutations using protein 3D structure ↗](https://doi.org/10.1093/bioinformatics/btae232)**Guanglei Yu, Qichang Zhao, Xuehua Bi et al.*21 citations*
115. **[Insights into the inner workings of transformer models for protein function prediction ↗](https://doi.org/10.1093/bioinformatics/btae031)**Markus A. Wenzel, Erik Grüner, Nils Strodthoff*21 citations*
116. **[MolFeSCue: enhancing molecular property prediction in data-limited and imbalanced contexts using few-shot and contrastive learning ↗](https://doi.org/10.1093/bioinformatics/btae118)**Ruochi Zhang, Chao Wu, Qian Yang et al.*21 citations*
117. **[PheWAS analysis on large-scale biobank data with PheTK ↗](https://doi.org/10.1093/bioinformatics/btae719)**Tam C. Tran, David J. Schlueter, Chenjie Zeng et al.*21 citations*
118. **[RetroCaptioner: beyond attention in end-to-end retrosynthesis transformer via contrastively captioned learnable graph representation ↗](https://doi.org/10.1093/bioinformatics/btae561)**Xiaoyi Liu, Chengwei Ai, Hongpeng Yang et al.*21 citations*
119. **[Scalable de novo classification of antibiotic resistance of Mycobacterium tuberculosis ↗](https://doi.org/10.1093/bioinformatics/btae243)**Mohammadali Serajian, Simone Marini, Jarno Alanko et al.*21 citations*
120. **[TAWFN: a deep learning framework for protein function prediction ↗](https://doi.org/10.1093/bioinformatics/btae571)**Lu Meng, Xiaoran Wang*21 citations*
121. **[TarKG: a comprehensive biomedical knowledge graph for target discovery ↗](https://doi.org/10.1093/bioinformatics/btae598)**Cong Zhou, Chuipu Cai, Xiaotian Huang et al.*21 citations*
122. **[Tutorial on survival modeling with applications to omics data ↗](https://doi.org/10.1093/bioinformatics/btae132)**Zhi Qiang Zhao, John Zobolas, Manuela Zucknick et al.*21 citations*
123. **[phylaGAN: data augmentation through conditional GANs and autoencoders for improving disease prediction accuracy using microbiome data ↗](https://doi.org/10.1093/bioinformatics/btae161)**Divya Sharma, Wendy Y. W. Lou, Wei Xu*21 citations*
124. **[scTPC: a novel semisupervised deep clustering model for scRNA-seq data ↗](https://doi.org/10.1093/bioinformatics/btae293)**Yushan Qiu, Lingfei Yang, Hao Jiang et al.*21 citations*
125. **[A BLAST from the past: revisiting blastp’s E-value ↗](https://doi.org/10.1093/bioinformatics/btae729)**Yang Young Lu, William Stafford Noble, Uri Keich*20 citations*
126. **[Cluster-efficient pangenome graph construction with nf-core/pangenome ↗](https://doi.org/10.1093/bioinformatics/btae609)**Simon Heumos, Michael Heuer, Friederike Hanssen et al.*20 citations*
127. **[DeepDR: a deep learning library for drug response prediction ↗](https://doi.org/10.1093/bioinformatics/btae688)**Zhengxiang Jiang, Pengyong Li*20 citations*
128. **[FMAlign2: a novel fast multiple nucleotide sequence alignment method for ultralong datasets ↗](https://doi.org/10.1093/bioinformatics/btae014)**Pinglu Zhang, Huan Liu, Yanming Wei et al.*20 citations*
129. **[Geometry-complete perceptron networks for 3D molecular graphs ↗](https://doi.org/10.1093/bioinformatics/btae087)**Alex Morehead, Jianlin Jack Cheng*20 citations*
130. **[MammalMethylClock R package: software for DNA methylation-based epigenetic clocks in mammals ↗](https://doi.org/10.1093/bioinformatics/btae280)**Joseph Alan Zoller, Steve Horvath*20 citations*
131. **[RawHash2: mapping raw nanopore signals using hash-based seeding and adaptive quantization ↗](https://doi.org/10.1093/bioinformatics/btae478)**Can Fırtına, Melina Soysal, Joël Lindegger et al.*20 citations*
132. **[p-IgGen: a paired antibody generative language model ↗](https://doi.org/10.1093/bioinformatics/btae659)**Oliver M. Turnbull, Dino Oglić, Rebecca Croasdale-Wood et al.*20 citations*
133. **[ChatMol: interactive molecular discovery with natural language ↗](https://doi.org/10.1093/bioinformatics/btae534)**Zheni Zeng, Bangchen Yin, Shipeng Wang et al.*19 citations*
134. **[DDGemb: predicting protein stability change upon single- and multi-point variations with embeddings and deep learning ↗](https://doi.org/10.1093/bioinformatics/btaf019)**Castrense Savojardo, Matteo Manfredi, Pier Luigi Martelli et al.*19 citations*
135. **[DeepLocRNA: an interpretable deep learning model for predicting RNA subcellular localization with domain-specific transfer-learning ↗](https://doi.org/10.1093/bioinformatics/btae065)**Jun Wang, Marc Horlacher, Lixin Cheng et al.*19 citations*
136. **[FungiFun3: systemic gene set enrichment analysis for fungal species ↗](https://doi.org/10.1093/bioinformatics/btae620)**Albert García López, Daniela Albrecht-Eckardt, Gianni Panagiotou et al.*19 citations*
137. **[HELM-GPT: de novo macrocyclic peptide design using generative pre-trained transformer ↗](https://doi.org/10.1093/bioinformatics/btae364)**Xiaopeng Xu, Chencheng Xu, Wenjia He et al.*19 citations*
138. **[HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools ↗](https://doi.org/10.1093/bioinformatics/btae564)**Mario Sänger, Samuele Garda, Xing David Wang et al.*19 citations*
139. **[SEraster: a rasterization preprocessing framework for scalable spatial omics data analysis ↗](https://doi.org/10.1093/bioinformatics/btae412)**Gohta Aihara, Kalen Clifton, Mayling Chen et al.*19 citations*
140. **[AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification ↗](https://doi.org/10.1093/bioinformatics/btae068)**Xiaoshu Zhu, Shuang Meng, Gaoshi Li et al.*18 citations*
141. **[Anti-symmetric framework for balanced learning of protein–protein interactions ↗](https://doi.org/10.1093/bioinformatics/btae603)**Tao Tang, Tianyang Li, Weizhuo Li et al.*18 citations*
142. **[AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects ↗](https://doi.org/10.1093/bioinformatics/btae244)**Ding Bai, Caleb N. Ellington, Shentong Mo et al.*18 citations*
143. **[Chain-aware graph neural networks for molecular property prediction ↗](https://doi.org/10.1093/bioinformatics/btae574)**Honghao Wang, Acong Zhang, Yuan Zhong et al.*18 citations*
144. **[DPNN-ac4C: a dual-path neural network with self-attention mechanism for identification of N4-acetylcytidine (ac4C) in mRNA ↗](https://doi.org/10.1093/bioinformatics/btae625)**Jiahao Yuan, Ziyi Wang, Zhuoyu Pan et al.*18 citations*
145. **[MEG-PPIS: a fast protein–protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network ↗](https://doi.org/10.1093/bioinformatics/btae269)**Hongzhen Ding, Xue Li, Peifu Han et al.*18 citations*
146. **[MolMVC: Enhancing molecular representations for drug-related tasks through multi-view contrastive learning ↗](https://doi.org/10.1093/bioinformatics/btae386)**Zhijian Huang, Ziyu Fan, Siyuan Shen et al.*18 citations*
147. **[Multi-Omic Graph Diagnosis (MOGDx): a data integration tool to perform classification tasks for heterogeneous diseases ↗](https://doi.org/10.1093/bioinformatics/btae523)**Barry Ryan, Riccardo Emilio Marioni, T. Ian Simpson*18 citations*
148. **[Multi-scale topology and position feature learning and relationship-aware graph reasoning for prediction of drug-related microbes ↗](https://doi.org/10.1093/bioinformatics/btae025)**Ping Xuan, Jing Gu, Hui Cui et al.*18 citations*
149. **[Single-cell and spatial multiomic inference of gene regulatory networks using SCRIPro ↗](https://doi.org/10.1093/bioinformatics/btae466)**Zhanhe Chang, Yunfan Xu, Xin Dong et al.*18 citations*
150. **[Advancing mRNA subcellular localization prediction with graph neural network and RNA structure ↗](https://doi.org/10.1093/bioinformatics/btae504)**Fuyi Li, Yue Bi, Xudong Guo et al.*17 citations*
151. **[AutoGVP: a dockerized workflow integrating ClinVar and InterVar germline sequence variant classification ↗](https://doi.org/10.1093/bioinformatics/btae114)**Jung Kim, Ammar S. Naqvi, Ryan J. Corbett et al.*17 citations*
152. **[DESpace : spatially variable gene detection via differential expression testing of spatial clusters ↗](https://doi.org/10.1093/bioinformatics/btae027)**Peiying Cai, Mark D. Robinson, Simone Tiberi*17 citations*
153. **[GraphCompass: spatial metrics for differential analyses of cell organization across conditions ↗](https://doi.org/10.1093/bioinformatics/btae242)**Mayar Ali, Merel Kuijs, Soroor Hediyeh-zadeh et al.*17 citations*
154. **[GraphPath: a graph attention model for molecular stratification with interpretability based on the pathway–pathway interaction network ↗](https://doi.org/10.1093/bioinformatics/btae165)**Teng Ma, Jianxin Wang*17 citations*
155. **[HAlign 4: a new strategy for rapidly aligning millions of sequences ↗](https://doi.org/10.1093/bioinformatics/btae718)**Tong Zhou, Pinglu Zhang, Quan Zou et al.*17 citations*
156. **[Improving generalizability of drug–target binding prediction by pre-trained multi-view molecular representations ↗](https://doi.org/10.1093/bioinformatics/btaf002)**Xike Ouyang, Y. X. Feng, Chen Cui et al.*17 citations*
157. **[MGRN: toward robust drug recommendation via multi-view gating retrieval network ↗](https://doi.org/10.1093/bioinformatics/btae572)**Fanjun Meng, Xiaobo Li, Xiaodi Hou et al.*17 citations*
158. **[MIKE: an ultrafast, assembly-, and alignment-free approach for phylogenetic tree construction ↗](https://doi.org/10.1093/bioinformatics/btae154)**Fang Wang, Yibin Wang, Xiaofei Zeng et al.*17 citations*
159. **[Protein structure alignment by Reseek improves sensitivity to remote homologs ↗](https://doi.org/10.1093/bioinformatics/btae687)**R. C. Edgar*17 citations*
160. **[ReactomeGSA: new features to simplify public data reuse ↗](https://doi.org/10.1093/bioinformatics/btae338)**Alexander Grentner, Eliot Ragueneau, Chuqiao Gong et al.*17 citations*
161. **[Ribotin: automated assembly and phasing of rDNA morphs ↗](https://doi.org/10.1093/bioinformatics/btae124)**Mikko Rautiainen*17 citations*
162. **[TPepPro: a deep learning model for predicting peptide–protein interactions ↗](https://doi.org/10.1093/bioinformatics/btae708)**Jin Xiao-hong, Zimeng Chen, Dan Yu et al.*17 citations*
163. **[Transfer learning of condition-specific perturbation in gene interactions improves drug response prediction ↗](https://doi.org/10.1093/bioinformatics/btae249)**Dongmin Bang, Bonil Koo, Sun Kim*17 citations*
164. **[ARGprofiler—a pipeline for large-scale analysis of antimicrobial resistance genes and their flanking regions in metagenomic datasets ↗](https://doi.org/10.1093/bioinformatics/btae086)**Hannah-Marie Martiny, Nikiforos Pyrounakis, Thomas Nordahl Petersen et al.*16 citations*
165. **[An Ensemble Spectral Prediction (ESP) model for metabolite annotation ↗](https://doi.org/10.1093/bioinformatics/btae490)**Xinmeng Li, Yan Zhou Chen, Apurva Kalia et al.*16 citations*
166. **[Autoencoder-based phenotyping of ophthalmic images highlights genetic loci influencing retinal morphology and provides informative biomarkers ↗](https://doi.org/10.1093/bioinformatics/btae732)**Panagiotis I. Sergouniotis, Adam Diakite, Kumar Gaurav et al.*16 citations*
167. **[CircSI-SSL: circRNA-binding site identification based on self-supervised learning ↗](https://doi.org/10.1093/bioinformatics/btae004)**Chao Cao, Chunyu Wang, Shuhong Yang et al.*16 citations*
168. **[Digger: directed annotation of immunoglobulin and T cell receptor V, D, and J gene sequences and assemblies ↗](https://doi.org/10.1093/bioinformatics/btae144)**William Lees, Swati Saha, Gur Yaari et al.*16 citations*
169. **[Dual-view jointly learning improves personalized drug synergy prediction ↗](https://doi.org/10.1093/bioinformatics/btae604)**Xueliang Li, Bihan Shen, Fangyoumin Feng et al.*16 citations*
170. **[Dynamic correlations: exact and approximate methods for mutual information ↗](https://doi.org/10.1093/bioinformatics/btae076)**Kemal Demirtaş, Burak Erman, Türkan Haliloǧlu*16 citations*
171. **[Exact global alignment using A* with chaining seed heuristic and match pruning ↗](https://doi.org/10.1093/bioinformatics/btae032)**Ragnar Groot Koerkamp, Pesho Ivanov*16 citations*
172. **[Figeno: multi-region genomic figures with long-read support ↗](https://doi.org/10.1093/bioinformatics/btae354)**Etienne Sollier, Jessica Heilmann, Clarissa Gerhäuser et al.*16 citations*
173. **[GraphADT: empowering interpretable predictions of acute dermal toxicity with multi-view graph pooling and structure remapping ↗](https://doi.org/10.1093/bioinformatics/btae438)**Xinqian Ma, Xiangzheng Fu, Tao Wang et al.*16 citations*
174. **[MVSF-AB: accurate antibody–antigen binding affinity prediction via multi-view sequence feature learning ↗](https://doi.org/10.1093/bioinformatics/btae579)**Minghui Li, Yao Shi, Shengqing Hu et al.*16 citations*
175. **[TransGEM: a molecule generation model based on Transformer with gene expression data ↗](https://doi.org/10.1093/bioinformatics/btae189)**Yanguang Liu, Hailong Yu, Xinya Duan et al.*16 citations*
176. **[2dGBH: Two-dimensional group Benjamini–Hochberg procedure for false discovery rate control in two-way multiple testing of genomic data ↗](https://doi.org/10.1093/bioinformatics/btae035)**Lu Yang, Pei Wang, Jun Chen*15 citations*
177. **[Are genomic language models all you need? Exploring genomic language models on protein downstream tasks ↗](https://doi.org/10.1093/bioinformatics/btae529)**Sam Boshar, Evan Trop, Bernardo P. de Almeida et al.*15 citations*
178. **[Disease gene prioritization with quantum walks ↗](https://doi.org/10.1093/bioinformatics/btae513)**Harto Saarinen, Mark Goldsmith, Rui‐Sheng Wang et al.*15 citations*
179. **[Floria: fast and accurate strain haplotyping in metagenomes ↗](https://doi.org/10.1093/bioinformatics/btae252)**Jim Shaw, Jean-Sébastien Gounot, Hanrong Chen et al.*15 citations*
180. **[Improved prediction of post-translational modification crosstalk within proteins using DeepPCT ↗](https://doi.org/10.1093/bioinformatics/btae675)**Yuxiang Huang, Rong Liu*15 citations*
181. **[Prediction of human O- linked glycosylation sites using stacked generalization and embeddings from pre-trained protein language model ↗](https://doi.org/10.1093/bioinformatics/btae643)**Subash Chandra Pakhrin, Neha Chauhan, Salman Khan et al.*15 citations*
182. **[PyCoMo: a python package for community metabolic model creation and analysis ↗](https://doi.org/10.1093/bioinformatics/btae153)**Michael Predl, Marianne Mießkes, Thomas Rattei et al.*15 citations*
183. **[RNA m6A detection using raw current signals and basecalling errors from Nanopore direct RNA sequencing reads ↗](https://doi.org/10.1093/bioinformatics/btae375)**Peng Ni, Jinrui Xu, Zeyu Zhong et al.*15 citations*
184. **[The FunCoup Cytoscape App: multi-species network analysis and visualization ↗](https://doi.org/10.1093/bioinformatics/btae739)**Davide Buzzao, Lukas Steininger, Dimitri Guala et al.*15 citations*
185. **[Using explainable machine learning to uncover the kinase–substrate interaction landscape ↗](https://doi.org/10.1093/bioinformatics/btae033)**Zhongliang Zhou, Wayland Yeung, Saber Soleymani et al.*15 citations*
186. **[imputomics: web server and R package for missing values imputation in metabolomics data ↗](https://doi.org/10.1093/bioinformatics/btae098)**Jarosław Chilimoniuk, Krystyna Grzesiak, Jakub Kała et al.*15 citations*
187. **[Compound-SNE: comparative alignment of t-SNEs for multiple single-cell omics data visualization ↗](https://doi.org/10.1093/bioinformatics/btae471)**Colin G. Cess, Laleh Haghverdi*14 citations*
188. **[ENKIE: a package for predicting enzyme kinetic parameter values and their uncertainties ↗](https://doi.org/10.1093/bioinformatics/btae652)**Mattia G. Gollub, Thierry Backes, Hans‐Michael Kaltenbach et al.*14 citations*
189. **[GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation ↗](https://doi.org/10.1093/bioinformatics/btae401)**Huiying Yan, Shaojun Wang, Hancheng Liu et al.*14 citations*
190. **[ICELLNET v2: a versatile method for cell–cell communication analysis from human transcriptomic data ↗](https://doi.org/10.1093/bioinformatics/btae089)**Lucile Massenet-Regad, Vassili Soumelis*14 citations*
191. **[Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation ↗](https://doi.org/10.1093/bioinformatics/btae190)**Andrew G Duncan, Jennifer A. Mitchell, Alan M Moses*14 citations*
192. **[Inferring gene regulatory networks from single-cell transcriptomics based on graph embedding ↗](https://doi.org/10.1093/bioinformatics/btae291)**Yanglan Gan, Jiacheng Yu, Guangwei Xu et al.*14 citations*
193. **[InterLabelGO+: unraveling label correlations in protein function prediction ↗](https://doi.org/10.1093/bioinformatics/btae655)**Quancheng Liu, Chengxin Zhang, Lydia Freddolino*14 citations*
194. **[MMOSurv: meta-learning for few-shot survival analysis with multi-omics data ↗](https://doi.org/10.1093/bioinformatics/btae684)**Gang Wen, Limin Li*14 citations*
195. **[Metagenomic functional profiling: to sketch or not to sketch? ↗](https://doi.org/10.1093/bioinformatics/btae397)**Mahmudur Rahman Hera, Shaopeng Liu, Wei Wei et al.*14 citations*
196. **[Optimizing multi-omics data imputation with NMF and GAN synergy ↗](https://doi.org/10.1093/bioinformatics/btae674)**Md. Istiaq Ansari, Khandakar Tanvir Ahmed, Wei Zhang*14 citations*
197. **[PCA-based spatial domain identification with state-of-the-art performance ↗](https://doi.org/10.1093/bioinformatics/btaf005)**Darius P. Schaub, Behnam Yousefi, Nico Kaiser et al.*14 citations*
198. **[Pitfalls of machine learning models for protein–protein interaction networks ↗](https://doi.org/10.1093/bioinformatics/btae012)**Loïc Lannelongue, Michael Inouye*14 citations*
199. **[Predicting single-cell cellular responses to perturbations using cycle consistency learning ↗](https://doi.org/10.1093/bioinformatics/btae248)**Wei Huang, Hui Liu*14 citations*
200. **[SCMeTA: a pipeline for single-cell metabolic analysis data processing ↗](https://doi.org/10.1093/bioinformatics/btae545)**Xingyu Pan, Si-Yuan Pan, Murong Du et al.*14 citations*

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