---
title: "Bioinformatics 2024 — all accepted papers, page 4"
description: "All 788 papers of Bioinformatics 2024 · page 4 of 8, the most cited first; those with our summary link to it."
canonical: "https://research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/4/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/4/)

[home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Bioinformatics](https://md.research.elamur.ai/free/en/venues/bioinformatics/) / [2024](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/) / [papers](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/) / page 4

# Bioinformatics 2024: all accepted papers

788 papers · page 4 of 8 · the most cited first · [← Bioinformatics 2024](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/)

[← prev](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/3/) [1](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/) [2](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/2/) [3](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/3/) **4** [5](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/5/) … [8](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/8/) [next →](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/5/)

301. **[AmplificationTimeR: an R package for timing sequential amplification events ↗](https://doi.org/10.1093/bioinformatics/btae281)**G. Maria Jakobsdottir, Stefan C. Dentro, Robert Glen Bristow et al.*9 citations*
302. **[CSV-Filter: a deep learning-based comprehensive structural variant filtering method for both short and long reads ↗](https://doi.org/10.1093/bioinformatics/btae539)**Zeyu Xia, Weiming Xiang, Qingzhe Wang et al.*9 citations*
303. **[CTEC: a cross-tabulation ensemble clustering approach for single-cell RNA sequencing data analysis ↗](https://doi.org/10.1093/bioinformatics/btae130)**Liang Wang, Chenyang Hong, Jiangning Song et al.*9 citations*
304. **[Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model ↗](https://doi.org/10.1093/bioinformatics/btae528)**Xin Ma, Sai Ritesh Thela, Fengdi Zhao et al.*9 citations*
305. **[Detecting transposable elements in long-read genomes using sTELLeR ↗](https://doi.org/10.1093/bioinformatics/btae686)**Kristine Bilgrav Sæther, Jesper Eisfeldt*9 citations*
306. **[Dynamic category-sensitive hypergraph inferring and homo-heterogeneous neighbor feature learning for drug-related microbe prediction ↗](https://doi.org/10.1093/bioinformatics/btae562)**Ping Xuan, Zelong Xu, Hui Cui et al.*9 citations*
307. **[FateNet: an integration of dynamical systems and deep learning for cell fate prediction ↗](https://doi.org/10.1093/bioinformatics/btae525)**Mehrshad Sadria, Thomas M. Bury*9 citations*
308. **[GNN4DM: a graph neural network-based method to identify overlapping functional disease modules ↗](https://doi.org/10.1093/bioinformatics/btae573)**András Gézsi, Péter Antal*9 citations*
309. **[HE2Gene: image-to-RNA translation via multi-task learning for spatial transcriptomics data ↗](https://doi.org/10.1093/bioinformatics/btae343)**Xingjian Chen, Jiecong Lin, Yuchen Wang et al.*9 citations*
310. **[Higher-order correction of persistent batch effects in correlation networks ↗](https://doi.org/10.1093/bioinformatics/btae531)**Soel Micheletti, Daniel Schlauch, John Quackenbush et al.*9 citations*
311. **[ICARUS v3, a massively scalable web server for single-cell RNA-seq analysis of millions of cells ↗](https://doi.org/10.1093/bioinformatics/btae167)**Andrew Jiang, Russell G. Snell, Klaus Lehnert*9 citations*
312. **[Icarust, a real-time simulator for Oxford Nanopore adaptive sampling ↗](https://doi.org/10.1093/bioinformatics/btae141)**Rory Munro, Satrio Haryo Benowo Wibowo, Alexander Payne et al.*9 citations*
313. **[Identification and annotation of centromeric hypomethylated regions with CDR-Finder ↗](https://doi.org/10.1093/bioinformatics/btae733)**Francesco Kumara Mastrorosa, Keisuke K. Oshima, Allison N. Rozanski et al.*9 citations*
314. **[Identifying nucleotide-binding leucine-rich repeat receptor and pathogen effector pairing using transfer-learning and bilinear attention network ↗](https://doi.org/10.1093/bioinformatics/btae581)**Baixue Qiao, Shuda Wang, Mingjun Hou et al.*9 citations*
315. **[Interactive visualization of nanopore sequencing signal data with Squigualiser ↗](https://doi.org/10.1093/bioinformatics/btae501)**Hiruna Samarakoon, Kisaru Liyanage, James M. Ferguson et al.*9 citations*
316. **[MCDHGN: heterogeneous network-based cancer driver gene prediction and interpretability analysis ↗](https://doi.org/10.1093/bioinformatics/btae362)**Lexiang Wang, Jingli Zhou, Xuan Wang et al.*9 citations*
317. **[Pacybara: accurate long-read sequencing for barcoded mutagenized allelic libraries ↗](https://doi.org/10.1093/bioinformatics/btae182)**Jochen Weile, Gabrielle Ferra, Gabriel E. Boyle et al.*9 citations*
318. **[Pf-HaploAtlas: an interactive web app for spatiotemporal analysis of Plasmodium falciparum genes ↗](https://doi.org/10.1093/bioinformatics/btae673)**Chiyun Lee, Eyyüb S. Ünlü, Nina F. D. White et al.*9 citations*
319. **[Selection among site-dependent structurally constrained substitution models of protein evolution by approximate Bayesian computation ↗](https://doi.org/10.1093/bioinformatics/btae096)**David Ferreiro, Catarina Branco, Miguel Arenas*9 citations*
320. **[Spaln3: improvement in speed and accuracy of genome mapping and spliced alignment of protein query sequences ↗](https://doi.org/10.1093/bioinformatics/btae517)**Osamu Gotoh*9 citations*
321. **[SpecEncoder: deep metric learning for accurate peptide identification in proteomics ↗](https://doi.org/10.1093/bioinformatics/btae220)**Kaiyuan Liu, Chenghua Tao, Yuzhen Ye et al.*9 citations*
322. **[TargetSA: adaptive simulated annealing for target-specific drug design ↗](https://doi.org/10.1093/bioinformatics/btae730)**Zhe Xue, Chenwei Sun, Wenhao Zheng et al.*9 citations*
323. **[Unraveling spatial domain characterization in spatially resolved transcriptomics with robust graph contrastive clustering ↗](https://doi.org/10.1093/bioinformatics/btae451)**Yingxi Zhang, Zhuohan Yu, Ka‐Chun Wong et al.*9 citations*
324. **[ViralWasm: a client-side user-friendly web application suite for viral genomics ↗](https://doi.org/10.1093/bioinformatics/btae018)**Daniel Ji, Robert Aboukhalil, Niema Moshiri*9 citations*
325. **[Zero is not absence: censoring-based differential abundance analysis for microbiome data ↗](https://doi.org/10.1093/bioinformatics/btae071)**Lap Sum Chan, Gen Li*9 citations*
326. **[pyM2aia: Python interface for mass spectrometry imaging with focus on deep learning ↗](https://doi.org/10.1093/bioinformatics/btae133)**Jonas Cordes, Thomas Enzlein, Carsten Hopf et al.*9 citations*
327. **[tstrait : a quantitative trait simulator for ancestral recombination graphs ↗](https://doi.org/10.1093/bioinformatics/btae334)**Daiki Tagami, Gertjan Bisschop, Jerome Kelleher*9 citations*
328. **[A deep learning method to integrate extracelluar miRNA with mRNA for cancer studies ↗](https://doi.org/10.1093/bioinformatics/btae653)**Tasbiraha Athaya, Xiaoman Li, Haiyan Hu*8 citations*
329. **[A learned score function improves the power of mass spectrometry database search ↗](https://doi.org/10.1093/bioinformatics/btae218)**Varun Ananth, Justin Sanders, Melih Yilmaz et al.*8 citations*
330. **[BERMAD: batch effect removal for single-cell RNA-seq data using a multi-layer adaptation autoencoder with dual-channel framework ↗](https://doi.org/10.1093/bioinformatics/btae127)**Xiangxin Zhan, Yanbin Yin, Han Zhang*8 citations*
331. **[BS-clock, advancing epigenetic age prediction with high-resolution DNA methylation bisulfite sequencing data ↗](https://doi.org/10.1093/bioinformatics/btae656)**Congcong Hu, Yunxiao Li, Longhui Li et al.*8 citations*
332. **[Bigtools: a high-performance BigWig and BigBed library in Rust ↗](https://doi.org/10.1093/bioinformatics/btae350)**Jack D. Huey, Nezar A. Abdennur*8 citations*
333. **[Computational prediction of multiple antigen epitopes ↗](https://doi.org/10.1093/bioinformatics/btae556)**Rajalakshmi Viswanathan, Moshe Carroll, A. Roffe et al.*8 citations*
334. **[ElemeNT 2023: an enhanced tool for detection and curation of core promoter elements ↗](https://doi.org/10.1093/bioinformatics/btae110)**Orit Adato, Anna Sloutskin, Hodaya Komemi et al.*8 citations*
335. **[Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model ↗](https://doi.org/10.1093/bioinformatics/btae211)**Tangqi Fang, Yifeng Liu, Addie Woicik et al.*8 citations*
336. **[Enhancing generalizability and performance in drug–target interaction identification by integrating pharmacophore and pre-trained models ↗](https://doi.org/10.1093/bioinformatics/btae240)**Zuolong Zhang, Xin He, Dazhi Long et al.*8 citations*
337. **[GradHC: highly reliable gradual hash-based clustering for DNA storage systems ↗](https://doi.org/10.1093/bioinformatics/btae274)**Dvir Ben Shabat, Adar Hadad, Avital Boruchovsky et al.*8 citations*
338. **[Graspot: a graph attention network for spatial transcriptomics data integration with optimal transport ↗](https://doi.org/10.1093/bioinformatics/btae394)**Zizhan Gao, Kai Cao, Lin Wan*8 citations*
339. **[Lambda3: homology search for protein, nucleotide, and bisulfite-converted sequences ↗](https://doi.org/10.1093/bioinformatics/btae097)**Hannes Hauswedell, Sara Hetzel, Simon Gene Gottlieb et al.*8 citations*
340. **[Learning meaningful representation of single-neuron morphology via large-scale pre-training ↗](https://doi.org/10.1093/bioinformatics/btae395)**Yimin Fan, Yaxuan Li, Yaxuan Li et al.*8 citations*
341. **[NLSDeconv: an efficient cell-type deconvolution method for spatial transcriptomics data ↗](https://doi.org/10.1093/bioinformatics/btae747)**Yunlu Chen, Feng Ruan, Ji-Ping Wang*8 citations*
342. **[Oncotree2vec — a method for embedding and clustering of tumor mutation trees ↗](https://doi.org/10.1093/bioinformatics/btae214)**Monica-Andreea Baciu-Drăgan, Niko Beerenwinkel*8 citations*
343. **[Optimizing representations for integrative structural modeling using Bayesian model selection ↗](https://doi.org/10.1093/bioinformatics/btae106)**Shreyas M. Arvindekar, Aditi Pathak, Kartik Majila et al.*8 citations*
344. **[PhosX: data-driven kinase activity inference from phosphoproteomics experiments ↗](https://doi.org/10.1093/bioinformatics/btae697)**Alessandro Lussana, Sophia Müller‐Dott, Julio Sáez-Rodríguez et al.*8 citations*
345. **[Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning ↗](https://doi.org/10.1093/bioinformatics/btae301)**Azza Althagafi, Fernando Zhapa-Camacho, Robert Hoehndorf*8 citations*
346. **[Representing mutations for predicting cancer drug response ↗](https://doi.org/10.1093/bioinformatics/btae209)**Patrick Wall, Trey Ideker*8 citations*
347. **[SAAMBE-MEM: a sequence-based method for predicting binding free energy change upon mutation in membrane protein–protein complexes ↗](https://doi.org/10.1093/bioinformatics/btae544)**Prawin Rimal, Shailesh Kumar Panday, Xu Wang et al.*8 citations*
348. **[SPRITE: improving spatial gene expression imputation with gene and cell networks ↗](https://doi.org/10.1093/bioinformatics/btae253)**Eric Sun, Rong Ma, James Zou*8 citations*
349. **[SpatialDDLS: an R package to deconvolute spatial transcriptomics data using neural networks ↗](https://doi.org/10.1093/bioinformatics/btae072)**Diego Mañanes, Inés Rivero-García, Carlos Relaño‐Rupérez et al.*8 citations*
350. **[Statistical framework to determine indel-length distribution ↗](https://doi.org/10.1093/bioinformatics/btae043)**Elya Wygoda, Gil Loewenthal, Asher Moshe et al.*8 citations*
351. **[TPepRet: a deep learning model for characterizing T-cell receptors–antigen binding patterns ↗](https://doi.org/10.1093/bioinformatics/btaf022)**Meng Wang, Wei Fan, Tianrui Wu et al.*8 citations*
352. **[Weighted families of contact maps to characterize conformational ensembles of (highly-)flexible proteins ↗](https://doi.org/10.1093/bioinformatics/btae627)**Javier González-Delgado, Pau Bernadó, Pierre Neuvial et al.*8 citations*
353. **[hopsy — a methods marketplace for convex polytope sampling in Python ↗](https://doi.org/10.1093/bioinformatics/btae430)**Richard Dominik Paul, Johann F. Jadebeck, Anton Stratmann et al.*8 citations*
354. **[longmixr: a tool for robust clustering of high-dimensional cross-sectional and longitudinal variables of mixed data types ↗](https://doi.org/10.1093/bioinformatics/btae137)**Jonas Hagenberg, Monika Budde, Teodora Pandeva et al.*8 citations*
355. **[scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution ↗](https://doi.org/10.1093/bioinformatics/btae028)**Zeyu Chen, Yuxin Miao, Zhiyuan Tan et al.*8 citations*
356. **[scDRMAE: integrating masked autoencoder with residual attention networks to leverage omics feature dependencies for accurate cell clustering ↗](https://doi.org/10.1093/bioinformatics/btae599)**Tianjiao Zhang, Hongfei Zhang, Jixiang Ren et al.*8 citations*
357. **[3D Optical Coherence Tomography image processing in BISCAP: characterization of biofilm structure and properties ↗](https://doi.org/10.1093/bioinformatics/btae041)**Diogo A. C. Narciso, Ana Pereira, Nuno O Dias et al.*7 citations*
358. **[A curated rotamer library for common post-translational modifications of proteins ↗](https://doi.org/10.1093/bioinformatics/btae444)**Oufan Zhang, Shubhankar A Naik, Zi Hao Liu et al.*7 citations*
359. **[A model-based hierarchical Bayesian approach to Sholl analysis ↗](https://doi.org/10.1093/bioinformatics/btae156)**Erik D. VonKaenel, Alexis M. Feidler, Rebecca L. Lowery et al.*7 citations*
360. **[Adaptive digital tissue deconvolution ↗](https://doi.org/10.1093/bioinformatics/btae263)**Franziska Görtler, Malte Mensching-Buhr, Ørjan Skaar et al.*7 citations*
361. **[AltGosling: automatic generation of text descriptions for accessible genomics data visualization ↗](https://doi.org/10.1093/bioinformatics/btae670)**Thomas Chris Smits, Sehi L’Yi, Andrew Patrick Mar et al.*7 citations*
362. **[CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbations ↗](https://doi.org/10.1093/bioinformatics/btae261)**Stefan Schrod, Helena U. Zacharias, Tim Beißbarth et al.*7 citations*
363. **[Castanet: a pipeline for rapid analysis of targeted multi-pathogen genomic data ↗](https://doi.org/10.1093/bioinformatics/btae591)**Richard Mayne, Shannah Secret, Cyndi G. Geoghegan et al.*7 citations*
364. **[Closing the computational biology ‘knowledge gap’: Spanish Wikipedia as a case study ↗](https://doi.org/10.1093/bioinformatics/btae247)**Nelly Selem Mojica, Tülay Karakulak, Audra Anjum et al.*7 citations*
365. **[Combined LC-MS/MS feature grouping, statistical prioritization, and interactive networking in msFeaST ↗](https://doi.org/10.1093/bioinformatics/btae584)**Kevin Mildau, Christoph Büschl, Jürgen Zanghellini et al.*7 citations*
366. **[Deep coupled registration and segmentation of multimodal whole-brain images ↗](https://doi.org/10.1093/bioinformatics/btae606)**Tingting Han, Jun Wu, Pengpeng Sheng et al.*7 citations*
367. **[DrugMGR: a deep bioactive molecule binding method to identify compounds targeting proteins ↗](https://doi.org/10.1093/bioinformatics/btae176)**Xiaokun Li, Qiang Yang, Long Xu et al.*7 citations*
368. **[Dynamic modelling of signalling pathways when ordinary differential equations are not feasible ↗](https://doi.org/10.1093/bioinformatics/btae683)**Timo Rachel, Eva Brombacher, Svenja Wöhrle et al.*7 citations*
369. **[End-to-end simulation of nanopore sequencing signals with feed-forward transformers ↗](https://doi.org/10.1093/bioinformatics/btae744)**Denis Beslic, Martin Kucklick, Susanne Engelmann et al.*7 citations*
370. **[EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data ↗](https://doi.org/10.1093/bioinformatics/btae191)**Sijie Li, Yuxi Li, Yu Sun et al.*7 citations*
371. **[GENEVIC: GENetic data Exploration and Visualization via Intelligent interactive Console ↗](https://doi.org/10.1093/bioinformatics/btae500)**Anindita Nath, Savannah Mwesigwa, Yulin Dai et al.*7 citations*
372. **[HIResist: a database of HIV-1 resistance to broadly neutralizing antibodies ↗](https://doi.org/10.1093/bioinformatics/btae103)**Milind Misra, Jeffy Jeffy, Charis Liao et al.*7 citations*
373. **[Identifying TAD-like domains on single-cell Hi-C data by graph embedding and changepoint detection ↗](https://doi.org/10.1093/bioinformatics/btae138)**Erhu Liu, Hongqiang Lyu, Yuan Liu et al.*7 citations*
374. **[Information-incorporated gene network construction with FDR control ↗](https://doi.org/10.1093/bioinformatics/btae125)**Hao Wang, Yumou Qiu, Hongqing Guo et al.*7 citations*
375. **[Integrating physics in deep learning algorithms: a force field as a PyTorch module ↗](https://doi.org/10.1093/bioinformatics/btae160)**Gabriele Orlando, Luis G. Serrano, Joost W. H. Schymkowitz et al.*7 citations*
376. **[Learning to explain is a good biomedical few-shot learner ↗](https://doi.org/10.1093/bioinformatics/btae589)**Peng Chen, Jian Wang, Ling Luo et al.*7 citations*
377. **[Ligand identification in CryoEM and X-ray maps using deep learning ↗](https://doi.org/10.1093/bioinformatics/btae749)**Jacek Karolczak, Anna Przybyłowska, Konrad Szewczyk et al.*7 citations*
378. **[Multi-indicator comparative evaluation for deep learning-based protein sequence design methods ↗](https://doi.org/10.1093/bioinformatics/btae037)**Jinyu Yu, Junxi Mu, Ting Wei et al.*7 citations*
379. **[NPSV-deep: a deep learning method for genotyping structural variants in short read genome sequencing data ↗](https://doi.org/10.1093/bioinformatics/btae129)**Michael D. Linderman, Jacob Wallace, Alderik van der Heyde et al.*7 citations*
380. **[NeoAgDT: optimization of personal neoantigen vaccine composition by digital twin simulation of a cancer cell population ↗](https://doi.org/10.1093/bioinformatics/btae205)**Anja Mösch, Filippo Grazioli, Pierre Machart et al.*7 citations*
381. **[NetMe 2.0: a web-based platform for extracting and modeling knowledge from biomedical literature as a labeled graph ↗](https://doi.org/10.1093/bioinformatics/btae194)**Antonio Di Maria, Lorenzo Bellomo, Fabrizio Billeci et al.*7 citations*
382. **[OpenDock: a pytorch-based open-source framework for protein–ligand docking and modelling ↗](https://doi.org/10.1093/bioinformatics/btae628)**Qiuyue Hu, Zechen Wang, Jintao Meng et al.*7 citations*
383. **[Pair-EGRET: enhancing the prediction of protein–protein interaction sites through graph attention networks and protein language models ↗](https://doi.org/10.1093/bioinformatics/btae588)**Ramisa Alam, Sazan Mahbub, Md. Shamsuzzoha Bayzid*7 citations*
384. **[Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs ↗](https://doi.org/10.1093/bioinformatics/btae383)**Tianci Song, Eric Cosatto, Gaoyuan Wang et al.*7 citations*
385. **[REUNION: transcription factor binding prediction and regulatory association inference from single-cell multi-omics data ↗](https://doi.org/10.1093/bioinformatics/btae234)**Yang Yang, Dana Pe’er*7 citations*
386. **[Scalable CNN-based classification of selective sweeps using derived allele frequencies ↗](https://doi.org/10.1093/bioinformatics/btae385)**Sjoerd van den Belt, Hanqing Zhao, Nikolaos Alachiotis*7 citations*
387. **[Scbean: a python library for single-cell multi-omics data analysis ↗](https://doi.org/10.1093/bioinformatics/btae053)**Haohui Zhang, Yuwei Wang, Bin Lian et al.*7 citations*
388. **[Scywalker: scalable end-to-end data analysis workflow for long-read single-cell transcriptome sequencing ↗](https://doi.org/10.1093/bioinformatics/btae549)**Peter De Rijk, Tijs Watzeels, Fahri Küçükali et al.*7 citations*
389. **[Second-order group knockoffs with applications to genome-wide association studies ↗](https://doi.org/10.1093/bioinformatics/btae580)**Benjamin B. Chu, Jiaqi Gu, Zhaomeng Chen et al.*7 citations*
390. **[TSpred: a robust prediction framework for TCR–epitope interactions using paired chain TCR sequence data ↗](https://doi.org/10.1093/bioinformatics/btae472)**Ha Young Kim, Sungsik Kim, Woong‐Yang Park et al.*7 citations*
391. **[TransTEx: novel tissue-specificity scoring method for grouping human transcriptome into different expression groups ↗](https://doi.org/10.1093/bioinformatics/btae475)**Pallavi Surana, Pratik Dutta, Ramana V. Davuluri*7 citations*
392. **[Triangulating evidence in health sciences with Annotated Semantic Queries ↗](https://doi.org/10.1093/bioinformatics/btae519)**Yi Liu, Tom R. Gaunt*7 citations*
393. **[Uncertainty-aware single-cell annotation with a hierarchical reject option ↗](https://doi.org/10.1093/bioinformatics/btae128)**Lauren Theunissen, Thomas Mortier, Yvan Saeys et al.*7 citations*
394. **[isolateR: an R package for generating microbial libraries from Sanger sequencing data ↗](https://doi.org/10.1093/bioinformatics/btae448)**Brendan A. Daisley, Sarah J. Vancuren, Dylan J. L. Brettingham et al.*7 citations*
395. **[sparsesurv: a Python package for fitting sparse survival models via knowledge distillation ↗](https://doi.org/10.1093/bioinformatics/btae521)**David Wissel, Nikita Janakarajan, Julius Schulte et al.*7 citations*
396. **[A machine-learning-based alternative to phylogenetic bootstrap ↗](https://doi.org/10.1093/bioinformatics/btae255)**Noa Ecker, Dorothée Huchon, Yishay Mansour et al.*6 citations*
397. **[A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis ↗](https://doi.org/10.1093/bioinformatics/btae663)**Nan Chen, Yu Xiao, Weimin Li et al.*6 citations*
398. **[Accelerated dimensionality reduction of single-cell RNA sequencing data with fastglmpca ↗](https://doi.org/10.1093/bioinformatics/btae494)**Eric Weine, Peter S. Carbonetto, Matthew Stephens*6 citations*
399. **[Accurate and efficient protein embedding using multi-teacher distillation learning ↗](https://doi.org/10.1093/bioinformatics/btae567)**Jiayu Shang, Cheng Peng, Yongxin Ji et al.*6 citations*
400. **[Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep ↗](https://doi.org/10.1093/bioinformatics/btae023)**Teng Liu, Zhaoyu Fang, Xin Li et al.*6 citations*

[← prev](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/3/) [1](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/) [2](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/2/) [3](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/3/) **4** [5](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/5/) … [8](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/8/) [next →](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/papers/page/5/)

- [← back to](https://md.research.elamur.ai/free/en/venues/bioinformatics/2024/) — Bioinformatics 2024