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ORCIDBioData Mining, Volume 15
Volume 15, Number 1, 2022
- Ralf E. Wellinger
, Jesús S. Aguilar-Ruiz:
A new challenge for data analytics: transposons. - Zong-Xian Yin, Hong-Ming Xu:
An unsupervised image segmentation algorithm for coronary angiography. - Songtham Anuntakarun, Supatcha Lertampaiporn, Teeraphan Laomettachit, Warin Wattanapornprom, Marasri Ruengjitchatchawalya:
mSRFR: a machine learning model using microalgal signature features for ncRNA classification. - David Chushig-Muzo, Cristina Soguero-Ruíz, Pablo de Miguel-Bohoyo, Inmaculada Mora-Jiménez:
Learning and visualizing chronic latent representations using electronic health records. - Rayan Eid, Claudine Landès, Alix Pernet, Emmanuel Benoît, Pierre Santagostini, Angelina El Ghaziri, Julie Bourbeillon:
DIVIS: a semantic DIstance to improve the VISualisation of heterogeneous phenotypic datasets. - Philip J. Freda, Henry R. Kranzler, Jason H. Moore:
Novel digital approaches to the assessment of problematic opioid use. - Marc Joiret, Jestinah M. Mahachie John, Elena S. Gusareva, Kristel Van Steen:
Correction: Confounding of linkage disequilibrium patterns in large scale DNA based gene-gene interaction studies. - David Vadnais, Michael Middleton, Oluwatosin Oluwadare:
ParticleChromo3D: a Particle Swarm Optimization algorithm for chromosome 3D structure prediction from Hi-C data. - Donald E. Brown, Suchetha Sharma, James A. Jablonski, Arthur Weltman:
Neural network methods for diagnosing patient conditions from cardiopulmonary exercise testing data. - Mauro Nascimben, Lia Rimondini, Davide Corà, Manolo Venturin:
Polygenic risk modeling of tumor stage and survival in bladder cancer. - Davide Chicco, Abbas Alameer, Sara Rahmati, Giuseppe Jurman:
Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning. - David N. Nicholson, Daniel S. Himmelstein, Casey S. Greene:
Expanding a database-derived biomedical knowledge graph via multi-relation extraction from biomedical abstracts. - Shaochuan Li, Yuning Yang, Xin Wang, Jun Li, Jun Yu, Xiangtao Li, Ka-Chun Wong:
Colorectal cancer subtype identification from differential gene expression levels using minimalist deep learning. - Joseph L. Bundy, Richard S. Judson, Antony J. Williams, Christopher M. Grulke, Imran Shah, Logan J. Everett:
Predicting molecular initiating events using chemical target annotations and gene expression. - Pratik Devkota, Somya D. Mohanty, Prashanti Manda:
A Gated Recurrent Unit based architecture for recognizing ontology concepts from biological literature. - Zhixuan Zeng, Xianming Tang, Yang Liu, Zhengkun He, Xun Gong:
Interpretable recurrent neural network models for dynamic prediction of the extubation failure risk in patients with invasive mechanical ventilation in the intensive care unit. - David Dora, Timea Dora, Gabor Szegvari, Csongor Gerdán, Zoltan Lohinai:
EZCancerTarget: an open-access drug repurposing and data-collection tool to enhance target validation and optimize international research efforts against highly progressive cancers. - Ying Zeng, Yuan Chen, Zheming Yuan:
iSuc-ChiDT: a computational method for identifying succinylation sites using statistical difference table encoding and the chi-square decision table classifier. - Wanchaloem Nadda, Waraporn Boonchieng, Ekkarat Boonchieng:
Influenza, dengue and common cold detection using LSTM with fully connected neural network and keywords selection. - Zeineb Safi, Neethu Venugopal, Haytham Ali, Michel Makhlouf, Faisal Farooq, Sabri Boughorbel:
Analysis of risk factors progression of preterm delivery using electronic health records. - Rakesh Kumar Saroj, Pawan Kumar Yadav, Rajneesh Singh, Obvious N. Chilyabanyama:
Machine Learning Algorithms for understanding the determinants of under-five Mortality. - Pelin Gundogdu, Carlos Loucera, Inmaculada Alamo-Alvarez, Joaquín Dopazo, Isabel Nepomuceno:
Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data. - Noura Mohammed Abdelwahed, Ghada Samy El-Tawel, Mohamed A. Makhlouf:
Effective hybrid feature selection using different bootstrap enhances cancers classification performance. - Bin Yang, Wenzheng Bao, Baitong Chen, Dan Song:
Single_cell_GRN: gene regulatory network identification based on supervised learning method and Single-cell RNA-seq data. - Roland Albert A. Romero, Mariefel Nicole Y. Deypalan, Suchit Mehrotra, John Titus Jungao, Natalie E. Sheils, Elisabetta Manduchi, Jason H. Moore:
Benchmarking AutoML frameworks for disease prediction using medical claims. - Alexa A. Woodward, Deanne M. Taylor, Elizabeth Goldmuntz, Laura E. Mitchell, A. J. Agopian, Jason H. Moore, Ryan J. Urbanowicz:
Gene-Interaction-Sensitive enrichment analysis in congenital heart disease. - Colinda C. J. M. Simons, Leo J. Schouten, Roger W. L. Godschalk, Frederik-Jan van Schooten, Monika Stoll, Kristel Van Steen, Piet A. van den Brandt, Matty P. Weijenberg:
Polymorphisms in the mTOR-PI3K-Akt pathway, energy balance-related exposures and colorectal cancer risk in the Netherlands Cohort Study. - Rawan AlSaad, Qutaibah M. Malluhi, Sabri Boughorbel:
PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks. - Hatice Büsra Lüleci, Alper Yilmaz:
Robust and rigorous identification of tissue-specific genes by statistically extending tau score. - Rahibu A. Abassi, Amina S. Msengwa:
Classification of breast cancer recurrence based on imputed data: a simulation study. - Sana Nazari Nezhad, Mohammad H. Zahedi, Elham Farahani:
Detecting diseases in medical prescriptions using data mining methods.
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