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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 K. 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 - Jody Clements, Cristian Goina, Philip M. Hubbard, Takashi Kawase, Donald J. Olbris, Hideo Otsuna, Robert Svirskas, Konrad Rokicki:
NeuronBridge: an intuitive web application for neuronal morphology search across large data sets. 114 - Karen Sargsyan, Carmay Lim:
Using protein language models for protein interaction hot spot prediction with limited data. 115 - Renjing Liu, Kun Qian, Xinwei He, Hongwei Li:
Integration of scRNA-seq data by disentangled representation learning with condition domain adaptation. 116 - Seungjun Ahn, Somnath Datta:
Differential network connectivity analysis for microbiome data adjusted for clinical covariates using jackknife pseudo-values. 117 - Shota Nose, Hirotsugu Shiroma, Takuji Yamada, Yushi Uno:
QNetDiff: a quantitative measurement of network rewiring. 118 - Junjie Shen, Shuo Wang, Yongfei Dong, Hao Sun, Xichao Wang, Zaixiang Tang:
A non-negative spike-and-slab lasso generalized linear stacking prediction modeling method for high-dimensional omics data. 119 - Lin-Lin Gu, Run-Qing Yang, Zhi-Yong Wang, Dan Jiang, Ming Fang:
Ensemble learning for integrative prediction of genetic values with genomic variants. 120 - Donny Chan, Graham L. Cromar, Billy Taj, John Parkinson:
Cell4D: a general purpose spatial stochastic simulator for cellular pathways. 121 - Shangru Li, Xiangpeng Meng, Rui Li, Bingding Huang, Xin Wang:
NanoBERTa-ASP: predicting nanobody paratope based on a pretrained RoBERTa model. 122 - H. M. A. Mohit Chowdhury, Terrance E. Boult, Oluwatosin Oluwadare:
Comparative study on chromatin loop callers using Hi-C data reveals their effectiveness. 123 - Yunus Emre Cebeci, Rumeysa Aslihan Erturk, Mehmet Arif Ergun, Mehmet Baysan:
Improving somatic exome sequencing performance by biological replicates. 124 - Raquel Lopes Costa, Luiz M. R. Gadelha Jr., Mirela D'arc, Marcelo Ribeiro-Alves, David L. Robertson, Jean-Marc Schwartz, Marcelo A. Soares, Fábio Porto:
HIHISIV: a database of gene expression in HIV and SIV host immune response. 125 - Jasper van Bemmelen, Davida S. Smyth, Jasmijn A. Baaijens:
Amplidiff: an optimized amplicon sequencing approach to estimating lineage abundances in viral metagenomes. 126 - Gang Tu, Xuan Wang, Rong Xia, Bowen Song:
m6A-TCPred: a web server to predict tissue-conserved human m6A sites using machine learning approach. 127 - Jader M. Caldonazzo Garbelini, Danilo Sipoli Sanches, Aurora T. R. Pozo:
biomapp::chip: large-scale motif analysis. 128 - Anna Kravchenko, Sjoerd Jacob de Vries, Malika Smaïl-Tabbone, Isaure Chauvot de Beauchêne:
HIPPO: HIstogram-based Pseudo-POtential for scoring protein-ssRNA fragment-based docking poses. 129 - Mehmet Arif Ergun, Omer Cinal, Berkant Bakisli, Abdullah Asim Emül, Mehmet Baysan:
COSAP: Comparative Sequencing Analysis Platform. 130 - Ahmed M. A. Elsherbini, Amr Hassan Elkholy, Youssef M. Fadel, Gleb Goussarov, Ahmed Mohamed Elshal, Mohamed El-Hadidi, Mohamed Mysara:
Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques. 131 - Yiran Huang, Pingfan Zeng, Cheng Zhong:
Classifying breast cancer subtypes on multi-omics data via sparse canonical correlation analysis and deep learning. 132 - Shuo Wang, Yuanning Liu, Hao Zhang, Zhen Liu:
SurvConvMixer: robust and interpretable cancer survival prediction based on ConvMixer using pathway-level gene expression images. 133 - James M. Dolezal, Sara Kochanny, Emma C. Dyer, Siddhi Ramesh, Andrew Srisuwananukorn, Matteo Sacco, Frederick M. Howard, Anran Li, Prajval Mohan, Alexander T. Pearson:
Slideflow: deep learning for digital histopathology with real-time whole-slide visualization. 134 - Xiao He, Ming Yan:
GraphKM: machine and deep learning for KM prediction of wildtype and mutant enzymes. 135 - Daniel Skubleny, Sunita Ghosh, Jennifer Spratlin, Daniel E. Schiller, Gina R. Rayat:
Feature-specific quantile normalization and feature-specific mean-variance normalization deliver robust bi-directional classification and feature selection performance between microarray and RNAseq data. 136 - Zhanshan (Sam) Ma:
Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes. 137 - Patrick Blumenkamp, Max Pfister, Sonja Diedrich, Karina Brinkrolf, Sebastian Jaenicke, Alexander Goesmann:
Curare and GenExVis: a versatile toolkit for analyzing and visualizing RNA-Seq data. 138 - Yanling Liu, Ruiyan Zhang, Xiaojing Dong, Hong Yang, Jing Li, Hongyan Cao, Jing Tian, Yanbo Zhang:
DAE-CFR: detecting microRNA-disease associations using deep autoencoder and combined feature representation. 139 - Yunyun Dong, Yunqing Chang, Yuxiang Wang, Qixuan Han, Xiaoyuan Wen, Ziting Yang, Yan Zhang, Yan Qiang, Kun Wu, Xiaole Fan, Xiaoqiang Ren:
MFSynDCP: multi-source feature collaborative interactive learning for drug combination synergy prediction. 140 - Xiaoting Zeng, Weilin Chen, Baiying Lei:
CAT-DTI: cross-attention and Transformer network with domain adaptation for drug-target interaction prediction. 141 - Garth L. Kong, Thai T. Nguyen, Wesley K. Rosales, Anjali D. Panikar, John H. W. Cheney, Theresa A. Lusardi, William M. Yashar, Brittany M. Curtiss, Sarah A. Carratt, Theodore P. Braun, Julia E. Maxson:
CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny. 142 - Ka Yin Chin, Shoichi Ishida, Yukio Sasaki, Kei Terayama:
Predicting condensate formation of protein and RNA under various environmental conditions. 143 - Wenyuan Sun, Kyongson Jon, Wensheng Zhu:
Multiple phenotype association tests based on sliced inverse regression. 144 - Muhammad Arif, Ge Fang, Ali Ghulam, Saleh Musleh, Tanvir Alam:
DPI_CDF: druggable protein identifier using cascade deep forest. 145 - Jing Chen, Haoyu Wu, Ning Wang:
KEGG orthology prediction of bacterial proteins using natural language processing. 146 - Pratyaydipta Rudra, Yi-Hui Zhou, Andrew B. Nobel, Fred A. Wright:
Control of false discoveries in grouped hypothesis testing for eQTL data. 147 - Jorge Beltrán, Lisandra Herrera Belén, Fernanda Parraguez Contreras, Jorge G. Farias, Jorge Machuca-Sepúlveda, Stefania Short:
MultiToxPred 1.0: a novel comprehensive tool for predicting 27 classes of protein toxins using an ensemble machine learning approach. 148 - Phuong-Nam Nguyen:
Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways. 149 - Caleb K. Kibet, Jean-Baka Domelevo Entfellner, Daudi Jjingo, Etienne Pierre de Villiers, Santie de Villiers, Karen Wambui, Sam Kinyanjui, Daniel Masiga:
Designing and delivering bioinformatics project-based learning in East Africa. 150 - Claus Vogl, Mariia Karapetiants, Burçin Yildirim, Hrönn Kjartansdóttir, Carolin Kosiol, Juraj Bergman, Michal Majka, Lynette Caitlin Mikula:
Inference of genomic landscapes using ordered Hidden Markov Models with emission densities (oHMMed). 151 - Mahira Kirmani, Gagandeep Kour, Mudasir Mohd, Nasrullah Sheikh, Dawood Ashraf Khan, Zahid Maqbool, Mohsin Altaf Wani, Abid Hussain Wani:
Biomedical semantic text summarizer. 152 - Rafael Peres da Silva, Chayaporn Suphavilai, Niranjan Nagarajan:
MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes. 153 - Jianqiao Hu, Sai Luo, Ming Tian, Adam Yongxin Ye:
TrieDedup: a fast trie-based deduplication algorithm to handle ambiguous bases in high-throughput sequencing. 154 - Moein E. Samadi, Hedieh Mirzaieazar, Alexander Mitsos, Andreas Schuppert:
Noisecut: a python package for noise-tolerant classification of binary data using prior knowledge integration and max-cut solutions. 155 - Xin Zeng, Guang-Peng Su, Shu-Juan Li, Shuang-Qing Lv, Meng-Liang Wen, Yi Li:
Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning. 156 - Li Pan, Haoyue Wang, Bo Yang, Wenbin Li:
A protein network refinement method based on module discovery and biological information. 157 - Xiaotian Wu, Wenju Hou, Ziqi Zhao, Lan Huang, Nan Sheng, Qixing Yang, Shuangquan Zhang, Yan Wang:
MMGAT: a graph attention network framework for ATAC-seq motifs finding. 158 - Tingpeng Yang, Yu Wang, Yonghong He:
TEC-miTarget: enhancing microRNA target prediction based on deep learning of ribonucleic acid sequences. 159 - Luan Pinto Rabelo, Davidson Sodré, Rodrigo Petry Corrêa de Sousa, Luciana Watanabe, Grazielle Gomes, Iracilda Sampaio, Marcelo Vallinoto:
SynGenes: a Python class for standardizing nomenclatures of mitochondrial and chloroplast genes and a web form for enhancing searches for evolutionary analyses. 160 - Andrew Zheng, Jim Shaw, Yun William Yu:
Mora: abundance aware metagenomic read re-assignment for disentangling similar strains. 161 - Terrence R. Ernst, John D. Blischak, Paul Nordlund, Joe Dalen, Justin Moore, Akshay Bhamidipati, Pankaj Dwivedi, Joe LoGrasso, Marco Rocha Curado, Brett Warren Engelmann:
OmicNavigator: open-source software for the exploration, visualization, and archival of omic studies. 162 - J. Ludwig, Jan Mrázek:
OrthoRefine: automated enhancement of prior ortholog identification via synteny. 163 - Yufang Liu, Yongkai Chen, Haoran Lu, Wenxuan Zhong, Guo-Cheng Yuan, Ping Ma:
Orthogonal multimodality integration and clustering in single-cell data. 164 - William L. Harrigan, Barbra D. Ferrell, K. Eric Wommack, Shawn W. Polson, Zachary D. Schreiber, Mahdi Belcaid:
Improvements in viral gene annotation using large language models and soft alignments. 165 - Leonardo Giannantoni, Roberta Bardini, Alessandro Savino, Stefano Di Carlo:
Biology System Description Language (BiSDL): a modeling language for the design of multicellular synthetic biological systems. 166 - S. R. Oshternian, S. Loipfinger, A. Bhattacharya, Rudolf S. N. Fehrmann:
Exploring combinations of dimensionality reduction, transfer learning, and regularization methods for predicting binary phenotypes with transcriptomic data. 167 - Adusei Bofa, Temesgen Zewotir:
Optimizing spatio-temporal correlation structures for modeling food security in Africa: a simulation-based investigation. 168 - Gao-Fei Wang, Longying Shen:
Cauchy hyper-graph Laplacian nonnegative matrix factorization for single-cell RNA-sequencing data analysis. 169 - Hyun Jung Lee, Utku Ozbulak, Homin Park, Stephen Depuydt, Wesley De Neve, Joris Vankerschaver:
Assessing the reliability of point mutation as data augmentation for deep learning with genomic data. 170 - Youngjun Park, Anne-Christin Hauschild:
The effect of data transformation on low-dimensional integration of single-cell RNA-seq. 171 - Sagara N. S. Gurusinghe, Julia M. Shifman:
Cold Spot SCANNER: Colab Notebook for predicting cold spots in protein-protein interfaces. 172 - Weiming He, Lian Xu, JingXian Wang, Zhen Yue, Yi Jing, Shuaishuai Tai, Jian Yang, Xiaodong Fang:
VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs. 173 - Robert Ebo Armah-Sekum, Sándor Szedmák, Juho Rousu:
Protein function prediction through multi-view multi-label latent tensor reconstruction. 174 - Matthieu Oliver, Nicolas Allou, Marjolaine Devineau, Jérôme Allyn, Cyril Ferdynus:
A transformer model for cause-specific hazard prediction. 175 - Jiajian Huang, Jinpeng Li, Qinchang Chen, Xia Wang, Guangyong Chen, Jin Tang:
Freeprotmap: waiting-free prediction method for protein distance map. 176 - Lei Qiao, Chang Li, Wei Lin, Xiaoqi He, Jia Mi, Yigang Tong, Jingyang Gao:
ViroISDC: a method for calling integration sites of hepatitis B virus based on feature encoding. 177 - Ryan D. Folks, Bhiken I. Naik, Donald E. Brown, Marcel Durieux:
Computer vision digitization of smartphone images of anesthesia paper health records from low-middle income countries. 178 - Samuel Rosean, Eric A. Sosa, Donal F. O'Shea, Srilakshmi M. Raj, Cathal Seoighe, John M. Greally:
Regulatory landscape enrichment analysis (RLEA): a computational toolkit for non-coding variant enrichment and cell type prioritization. 179 - Aldo Sergi, Luca Beltrame, Sergio Marchini, Marco Masseroli:
Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking. 180 - Richard Van, Daniel Alvarez, Travis Mize, Sravani Gannavarapu, Lohitha Chintham Reddy, Fatma Nasoz, Mira V. Han:
A comparison of RNA-Seq data preprocessing pipelines for transcriptomic predictions across independent studies. 181 - Weixiong Pang, Ming Chen, Yufang Qin:
Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning. 182 - Qi Guan, Xianzhong Yan, Yida Wu, Da Zhou, Jie Hu:
Biclustering analysis on tree-shaped time-series single cell gene expression data of Caenorhabditis elegans. 183 - Samuel Piquer-Esteban, Vicente Arnau, Wladimiro Díaz, Andrés Moya:
OMD Curation Toolkit: a workflow for in-house curation of public omics datasets. 184
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