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ORCIDBMC Bioinformatics, Volume 25
Volume 25, Number 1, December 2024
- Edwin Alvarez-Mamani, Reinhard Dechant, César Armando Beltrán Castañón, Alfredo J. Ibáñez
:
Graph embedding on mass spectrometry- and sequencing-based biomedical data. 1 - Madiha Shabbir, Aziz Mithani:
Roast: a tool for reference-free optimization of supertranscriptome assemblies. 2 - Pedro A. Saa, Sebastian Zapararte, Christopher C. Drovandi, Lars Keld Nielsen:
LooplessFluxSampler: an efficient toolbox for sampling the loopless flux solution space of metabolic models. 3 - Kimberly To, Judy Strickland, Emily Reinke, Alexandre Borrel, Jim Truax, Heather Maldonado, David G. Allen, Nicole C. Kleinstreuer:
Computational application of internationally harmonized defined approaches to skin sensitization: DASS App. 4 - Dengju Yao, Bailin Li, Xiaojuan Zhan, Xiaorong Zhan, Liyang Yu:
GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations. 5 - Yongjian Guan, Chang-Qing Yu, Li-Ping Li, Zhu-Hong You, Weixiao Meng, Xin-Fei Wang, Chen Yang, Lu-Xiang Guo:
MHESMMR: a multilevel model for predicting the regulation of miRNAs expression by small molecules. 6 - Xue-Qin Chen, Jie Ma, Di Xu, Zuo-Lin Xiang:
Correction: Comprehensive analysis of KLF2 as a prognostic biomarker associated with fibrosis and immune infiltration in advanced hepatocellular carcinoma. 7 - Qian Liu, Qiang Hu, Song Liu, Alan David Hutson, Martin Morgan:
ReUseData: an R/Bioconductor tool for reusable and reproducible genomic data management. 8 - Lasse Meyer, Nils Eling, Bernd Bodenmiller:
cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging data. 9 - Jiahao Wei, Linzhang Lu, Tie Shen:
Predicting drug-protein interactions by preserving the graph information of multi source data. 10 - Eli J. Draizen, John Readey, Cameron Mura, Philip E. Bourne:
Prop3D: A flexible, Python-based platform for machine learning with protein structural properties and biophysical data. 11 - Ali Hakem Alsaeedi, Haider Hameed R. Al-Mahmood, Zainab Fahad Alnaseri, Mohammad R. Aziz, Dhiah Al-Shammary, Ayman Ibaida, Khandakar Ahmed:
Fractal feature selection model for enhancing high-dimensional biological problems. 12 - Lixuan Mu, Jiangning Song, Tatsuya Akutsu, Tomoya Mori:
DiCleave: a deep learning model for predicting human Dicer cleavage sites. 13 - Xu Zhang, Ya Su, Andrew N. Lane, Arnold J. Stromberg, Teresa W.-M. Fan, Chi Wang:
Correction: Bayesian kinetic modeling for tracer-based metabolomic data. 14 - Josip Maric, Kresimir Krizanovic, Sylvain Riondet, Niranjan Nagarajan, Mile Sikic:
Comparative analysis of metagenomic classifiers for long-read sequencing datasets. 15 - Eduardo N. Castanho, João Lobo, Rui Henriques, Sara C. Madeira:
Correction: G-bic: generating synthetic benchmarks for biclustering. 16 - Mahmoud Gamal, Marwa A. Ibrahim:
Introducing the f0% method: a reliable and accurate approach for qPCR analysis. 17 - Sahar Mohseni-Takalloo, Hadis Mohseni, Hassan Mozaffari-Khosravi, Masoud Mirzaei, Mahdieh Hosseinzadeh:
The effect of data balancing approaches on the prediction of metabolic syndrome using non-invasive parameters based on random forest. 18 - Zachary L. Maas, Robin D. Dowell:
Internal and external normalization of nascent RNA sequencing run-on experiments. 19 - Joel Nulsen, Nosheen Hussain, Aws Al-Deka, Jason Yap, Khalil Uddin, Christopher Yau, Ahmed Ashour Ahmed:
Correction: Completing a genomic characterisation of microscopic tumour samples with copy number. 20 - Clayton Carter, Aaron Saporito, Stephen M. Douglass:
MetageneCluster: a Python package for filtering conflicting signal trends in metagene plots. 21 - Yu Han, Qiong Zhou, Leibo Liu, Jianwei Li, Yuan Zhou:
DNI-MDCAP: improvement of causal MiRNA-disease association prediction based on deep network imputation. 22 - Tay Xin Hui, Shahreen Kasim, Izzatdin Abdul Aziz, Mohd Farhan Md Fudzee, Nazleeni Samiha Haron, Tole Sutikno, Rohayanti Hassan, Hairulnizam Mahdin, Seah Choon Sen:
Robustness evaluations of pathway activity inference methods on gene expression data. 23 - Emma E. Kim, Chloe Soohyun Jang, Hakin Kim, Buhm Han:
PASTRY: achieving balanced power for detecting risk and protective minor alleles in meta-analysis of association studies with overlapping subjects. 24 - Jamshaid A. Shahir, Natalie Stanley, Jeremy E. Purvis:
Cellograph: a semi-supervised approach to analyzing multi-condition single-cell RNA-sequencing data using graph neural networks. 25 - David Rojas-Velazquez, Sarah Kidwai, Aletta D. Kraneveld, Alberto Tonda, Daniel L. Oberski, Johan Garssen, Alejandro Lopez Rincon:
Methodology for biomarker discovery with reproducibility in microbiome data using machine learning. 26 - Bingjun Li, Sheida Nabavi:
A multimodal graph neural network framework for cancer molecular subtype classification. 27 - Rukundo Prince, Zhendong Niu, Zahid Younas Khan, Masabo Emmanuel, Niyishaka Patrick:
COVID-19 detection from chest X-ray images using CLAHE-YCrCb, LBP, and machine learning algorithms. 28 - Yifan Li, Qianying Li, Lvying Wu, Haiyan Wang, Hui Shi, Chenhui Yang, Yiqun Gu, Jianyuan Li, Zhiliang Ji:
SperMD: the expression atlas of sperm maturation. 29 - Benedikt Venn, Thomas Leifeld, Ping Zhang, Timo Mühlhaus:
Temporal classification of short time series data. 30 - Thi-Hau Nguyen, Ha-Nam Nguyen, Trung-Nghia Vu:
CircNetVis: an interactive web application for visualizing interaction networks of circular RNAs. 31 - Honglei Wang, Tao Huang, Dong Wang, Wenliang Zeng, Yanjing Sun, Lin Zhang:
MSCAN: multi-scale self- and cross-attention network for RNA methylation site prediction. 32 - Morteza Rakhshaninejad, Mohammad Fathian, Reza Shirkoohi, Farnaz Barzinpour, Amir H. Gandomi:
Refining breast cancer biomarker discovery and drug targeting through an advanced data-driven approach. 33 - Yiran Huang, Fuhao Chen, Hongtao Sun, Cheng Zhong:
Exploring gene-patient association to identify personalized cancer driver genes by linear neighborhood propagation. 34 - Xiaoping Min, Chongzhou Yang, Jun Xie, Yang Huang, Nan Liu, Xiaocheng Jin, Tianshu Wang, Zhibo Kong, Xiaoli Lu, Shengxiang Ge, Jun Zhang, Ningshao Xia:
Tpgen: a language model for stable protein design with a specific topology structure. 35 - Clémence Joseph, Haris Zafeiropoulos, Kristel Bernaerts, Karoline Faust:
Predicting microbial interactions with approaches based on flux balance analysis: an evaluation. 36 - Naghme Nazer, Mohammad Hossein Sepehri, Hoda Mohammadzade, Mahya Mehrmohamadi:
A novel approach toward optimal workflow selection for DNA methylation biomarker discovery. 37 - Tianhua Yao, Xicheng Chen, Haojia Wang, Chengcheng Gao, Jia Chen, Dali Yi, Zeliang Wei, Ning Yao, Yang Li, Dong Yi, Yazhou Wu:
Deep evolutionary fusion neural network: a new prediction standard for infectious disease incidence rates. 38 - Jing Zhu, Chao Che, Hao Jiang, Jian Xu, Jiajun Yin, Zhaoqian Zhong:
SSF-DDI: a deep learning method utilizing drug sequence and substructure features for drug-drug interaction prediction. 39 - Wei Han, Sanguo Zhang, Hailong Gao, Deliang Bu:
Clustering on hierarchical heterogeneous data with prior pairwise relationships. 40 - Lifei Wang, Rui Nie, Xuexia Miao, Yankai Cai, Anqi Wang, Hanwen Zhang, Jiang Zhang, Jun Cai:
InClust+: the deep generative framework with mask modules for multimodal data integration, imputation, and cross-modal generation. 41 - Haiyang Chang, Daniel A. Ashlock, Steffen P. Graether, Stefan M. Keller:
Anchor Clustering for million-scale immune repertoire sequencing data. 42 - Georg Hahn, Sharon Marie Lutz, Julian Hecker, Dmitry Prokopenko, Michael H. Cho, Edwin K. Silverman, Scott T. Weiss, Christoph Lange:
Fast computation of the eigensystem of genomic similarity matrices. 43 - Yuke Xie, Xueqing Peng, Peiluan Li:
MIWE: detecting the critical states of complex biological systems by the mutual information weighted entropy. 44 - Patrick E. Gelbach, Handan Cetin, Stacey D. Finley:
Flux sampling in genome-scale metabolic modeling of microbial communities. 45 - Dengju Yao, Yuexiao Deng, Xiaojuan Zhan, Xiaorong Zhan:
Predicting lncRNA-disease associations using multiple metapaths in hierarchical graph attention networks. 46 - Rogia Kpanou, Patrick Dallaire, Elsa Rousseau, Jacques Corbeil:
Learning self-supervised molecular representations for drug-drug interaction prediction. 47 - Alireza Dehghan, Karim Abbasi, Parvin Razzaghi, Hossein Banadkuki, Sajjad Gharaghani:
CCL-DTI: contributing the contrastive loss in drug-target interaction prediction. 48 - Abigail Glascock, Eric Waltari, Gytis Dudas, Joan Wong, Vida Ahyong:
PoMeLo: a systematic computational approach to predicting metabolic loss in pathogen genomes. 49 - Lei Chen, Chenyu Zhang, Jing Xu:
PredictEFC: a fast and efficient multi-label classifier for predicting enzyme family classes. 50 - Tim U. H. Baumeister, Eivind Aadland, Roger G. Linington, Olav M. Kvalheim:
Multivariate pattern analysis: a method and software to reveal, quantify, and visualize predictive association patterns in multicollinear data. 51 - Hyunwhan Joe, Hong-Gee Kim:
Multi-label classification with XGBoost for metabolic pathway prediction. 52 - Rose-Marie Fraboulet, Yanis Si Ahmed, Marc Aubry, Sebastien Corre, Marie-Dominique Galibert, Yuna Blum:
Cirscan: a shiny application to identify differentially active sponge mechanisms and visualize circRNA-miRNA-mRNA networks. 53 - Karl Johan Westrin, Warren Kretzschmar, Olof Emanuelsson:
ClusTrast: a short read de novo transcript isoform assembler guided by clustered contigs. 54 - Andrew D. McCall:
Colocalization by cross-correlation, a new method of colocalization suited for super-resolution microscopy. 55 - Yongjun Choi, Junho Cha, Sungkyoung Choi:
Evaluation of penalized and machine learning methods for asthma disease prediction in the Korean Genome and Epidemiology Study (KoGES). 56 - Sedighe Rastahi, Azadeh Saki, Hamed Tabesh:
Modifying the false discovery rate procedure based on the information theory under arbitrary correlation structure and its performance in high-dimensional genomic data. 57 - Vincent Y. Pappalardo, Leyla Azarang, Egija Zaura, Bernd W. Brandt, Renée X. de Menezes:
A new approach to describe the taxonomic structure of microbiome and its application to assess the relationship between microbial niches. 58 - Dimitrios Iliadis, Bernard De Baets, Tapio Pahikkala, Willem Waegeman:
A comparison of embedding aggregation strategies in drug-target interaction prediction. 59 - Ruimin Wang, Hengxuan Jiang, Miaoshan Lu, Junjie Tong, Shaowei An, Jinyin Wang, Changbin Yu:
MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry. 60 - Amira Sami, Sara El-Metwally, M. Z. Rashad:
MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads. 61 - Ghanshyam Verma, Dietrich Rebholz-Schuhmann, Michael G. Madden:
Enabling personalised disease diagnosis by combining a patient's time-specific gene expression profile with a biomedical knowledge base. 62 - Valeriia Sherina, Helene R. McMurray, Winslow Powers, Hartmut Land, Tanzy M. T. Love, Matthew N. McCall:
Correction: Multiple imputation and direct estimation for qPCR data with non-detects. 63 - Dharmesh D. Bhuva, Chin Wee Tan, Ning Liu, Holly J. Whitfield, Nicholas Papachristos, Samuel C. Lee, Malvika Kharbanda, Ahmed Mohamed, Melissa J. Davis:
vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis. 64 - Yongwen Zhuang, Na Yeon Kim, Lars G. Fritsche, Bhramar Mukherjee, Seunggeun Lee:
Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction. 65 - Jesse R. Walsh, Guangchao Sun, Jagadheshwar Balan, Jayson Hardcastle, Jason Vollenweider, Calvin Jerde, Kandelaria Rumilla, Christy Koellner, Alaa Koleilat, Linda Hasadsri, Benjamin Kipp, W. Garrett Jenkinson, Eric W. Klee:
A supervised learning method for classifying methylation disorders. 66 - Michael A. Reiter, Julia A. Vorholt:
Dashing Growth Curves: a web application for rapid and interactive analysis of microbial growth curves. 67 - Milad Eidi, Samaneh Abdolalizadeh, Soheila Moeini, Masoud Garshasbi, Javad Zahiri:
123VCF: an intuitive and efficient tool for filtering VCF files. 68 - Hengkang Wang, Han Lu, Ju Sun, Sandra E. Safo:
Interpretable deep learning methods for multiview learning. 69 - Anthony Baptista, Galadriel Brière, Anaïs Baudot:
Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond. 70 - Kord M. Kober, Liam Berger, Ritu Roy, Adam B. Olshen:
Torch-eCpG: a fast and scalable eQTM mapper for thousands of molecular phenotypes with graphical processing units. 71 - Valentina Crippa, Emanuela Fina, Daniele Ramazzotti, Rocco Piazza:
Control-FREEC viewer: a tool for the visualization and exploration of copy number variation data. 72 - Adam Bessa-Silva:
Fasta2Structure: a user-friendly tool for converting multiple aligned FASTA files to STRUCTURE format. 73 - Arnab Kole, Arup Kumar Bag, Anindya Jyoti Pal, Debashis De:
Generic model to unravel the deeper insights of viral infections: an empirical application of evolutionary graph coloring in computational network biology. 74 - Haiou Qi, Ting Yu, Wenwen Yu, Chenxi Liu:
Drug-target affinity prediction with extended graph learning-convolutional networks. 75 - Audrey E. Bollas, Andrei Rajkovic, Defne Ceyhan, Jeffrey B. Gaither, Elaine R. Mardis, Peter White:
SNVstory: inferring genetic ancestry from genome sequencing data. 76 - Huanrong Tang, Yaowu Wang, Jianquan Ouyang, Jinlin Wang:
Simcryocluster: a semantic similarity clustering method of cryo-EM images by adopting contrastive learning. 77 - Haiyue Kuang, Zhen Zhang, Bin Zeng, Xin Liu, Hao Zuo, Xingye Xu, Lei Wang:
A novel microbe-drug association prediction model based on graph attention networks and bilayer random forest. 78 - Shihui He, Lijun Yun, Haicheng Yi:
Fusing graph transformer with multi-aggregate GCN for enhanced drug-disease associations prediction. 79 - Philippe Hauchamps, Babak Bayat, Simon Delandre, Mehdi Hamrouni, Marie Toussaint, Stephane Temmerman, Dan Lin, Laurent Gatto:
CytoPipeline and CytoPipelineGUI: a Bioconductor R package suite for building and visualizing automated pre-processing pipelines for flow cytometry data. 80 - Il-Youp Kwak, Byeong-Chan Kim, Juhyun Lee, Taein Kang, Daniel J. Garry, Jianyi Zhang, Wuming Gong:
Proformer: a hybrid macaron transformer model predicts expression values from promoter sequences. 81 - Katelyn McNair, Peter Salamon, Robert A. Edwards, Anca M. Segall:
PRFect: a tool to predict programmed ribosomal frameshifts in prokaryotic and viral genomes. 82 - Sedighe Rastaghi, Azadeh Saki, Hamed Tabesh:
Correction: Modifying the false discovery rate procedure based on the information theory under arbitrary correlation structure and its performance in high-dimensional genomic data. 83 - K. M. Tahsin Hassan Rahit, Vladimir Avramovic, Jessica X. Chong, Maja Tarailo-Graovac:
GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM. 84 - Benjamin Giovanni Iovino, Yuzhen Ye:
Protein embedding based alignment. 85 - Louis J. M. Aslett, Ryan R. Christ:
kalis: a modern implementation of the Li & Stephens model for local ancestry inference in R. 86 - Neda Emami, Reza Ferdousi:
HormoNet: a deep learning approach for hormone-drug interaction prediction. 87 - Hua Chai, Siyin Lin, Junqi Lin, Minfan He, Yuedong Yang, Yongzhong OuYang, Huiying Zhao:
An uncertainty-based interpretable deep learning framework for predicting breast cancer outcome. 88 - Jean-Noël Lorenzi, François Graner, Virginie Courtier-Orgogozo, Guillaume Achaz:
CNCA aligns small annotated genomes. 89 - Theresa Scharl, Bettina Grün:
A clustering procedure for three-way RNA sequencing data using data transformations and matrix-variate Gaussian mixture models. 90 - Qingru Xu, Xiaoqiong Bao, Zhuobin Lin, Lin Tang, Li-na He, Jian Ren, Zhixiang Zuo, Kunhua Hu:
AStruct: detection of allele-specific RNA secondary structure in structuromic probing data. 91 - Leandro Y. S. Okimoto, Rayol Mendonca-Neto, Fabíola G. Nakamura, Eduardo Freire Nakamura, David Fenyö, Cláudio Teixeira Silva:
Few-shot genes selection: subset of PAM50 genes for breast cancer subtypes classification. 92 - Katharina Munk, Daria Ilina, Lisa Ziemba, Günter Brader, Eva M. Molin:
Holomics - a user-friendly R shiny application for multi-omics data integration and analysis. 93 - Lu Li, Shi Yan, Barbara M. Bakker, Huub C. J. Hoefsloot, Bo Chawes, David Horner, Morten A. Rasmussen, Age K. Smilde, Evrim Acar:
Analyzing postprandial metabolomics data using multiway models: a simulation study. 94 - Akram Ashyani, Yu-Heng Wu, Huan-Wei Hsu, Torbjörn E. M. Nordling:
Ideal adaptive control in biological systems: an analysis of $\mathbb {P}$-invariance and dynamical compensation properties. 95 - Konstantin Yuditskiy, Igor Bezdvornykh, Anastasiya Kazantseva, Alexander Kanapin, Anastasia Samsonova:
BSXplorer: analytical framework for exploratory analysis of BS-seq data. 96 - Chengzhou Wu, Xichen Mou, Hongmei Zhang:
Gbdmr: identifying differentially methylated CpG regions in the human genome via generalized beta regressions. 97 - David L. Hölscher, Michael Goedertier, Barbara Mara Klinkhammer, Patrick Droste, Ivan G. Costa, Peter Boor, Roman David Bülow:
tRigon: an R package and Shiny App for integrative (path-)omics data analysis. 98 - Xiaolu Xu, Zitong Qi, Lei Wang, Meiwei Zhang, Zhaohong Geng, Xiumei Han:
Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact. 99 - Dong Wang, Jie Li, Edwin Wang, Yadong Wang:
DVA: predicting the functional impact of single nucleotide missense variants. 100 - Yeon-Ji Park, Geun-Je Yang, Chae-Bong Sohn, Soo Jun Park:
GPDminer: a tool for extracting named entities and analyzing relations in biological literature. 101 - Shahid Akbar, Ali Raza, Quan Zou:
Deepstacked-AVPs: predicting antiviral peptides using tri-segment evolutionary profile and word embedding based multi-perspective features with deep stacking model. 102 - Onder Tutsoy, Gizem Gul Koç:
Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification. 103 - Hanwen Xing, Christopher Yau:
Bayesian inference for identifying tumour-specific cancer dependencies through integration of ex-vivo drug response assays and drug-protein profiling. 104 - Chuanqi Lao, Pengfei Zheng, Hongyang Chen, Qiao Liu, Feng An, Zhao Li:
DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies. 105 - Thanh Hai Dang, Tien Anh Vu:
xCAPT5: protein-protein interaction prediction using deep and wide multi-kernel pooling convolutional neural networks with protein language model. 106 - Steven Gore, Bailey Meche, Danyang Shao, Benjamin Ginnett, Kelly Zhou, Rajeev K. Azad:
DiseaseNet: a transfer learning approach to noncommunicable disease classification. 107 - Ying Liang, XingRui Yin, YangSen Zhang, You Guo, YingLong Wang:
Predicting lncRNA-protein interactions through deep learning framework employing multiple features and random forest algorithm. 108 - Jason R. Miller, Donald A. Adjeroh:
Machine learning on alignment features for parent-of-origin classification of simulated hybrid RNA-seq. 109 - Simone Alessandri, Maria L. Ratto, Sergio Rabellino, Gabriele Piacenti, Sandro Gepiro Contaldo, Simone Pernice, Marco Beccuti, Raffaele A. Calogero, Luca Alessandrì:
CREDO: a friendly Customizable, REproducible, DOcker file generator for bioinformatics applications. 110 - Sheikh Hasib Ahmed, Dibyendu Brinto Bose, Rafi Khandoker, M. Saifur Rahman:
StackDPP: a stacking ensemble based DNA-binding protein prediction model. 111 - Ornella Irrera, Stefano Marchesin, Gianmaria Silvello:
MetaTron: advancing biomedical annotation empowering relation annotation and collaboration. 112 - Kevin Z. Lin, Yixuan Qiu, Kathryn Roeder:
eSVD-DE: cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings. 113