Effects of acute PM2.5 purification on cognitive function and underlying mechanisms: Evidence from integrating alternative splicing into multi-omics

Authors: Ke, Limei ^{a, b, 1}, Liu, Jianxiu ^{c, 1}, Feng, Guoqing ^{a, b}, Li, Xingtian ^c, Zhang, Yao ^{c, d}, Zhang, Shiqi ^c, Ma, Xindong ^{c, e}, Di, Qian ^{f, g, ⁎}

Source: In Journal of Hazardous Materials 5 April 2025 487

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

Authors: Bulbul Ahmmed, Elisabeth G. Rau, Maruti K. Mudunuru, Satish Karra, Joshua R. Tempelman, Adam J. Wachtor, Jean-Baptiste Forien, Gabe M. Guss, Nicholas P. Calta, Phillip J. DePond, Manyalibo J. Matthews

Source: Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)

Subject Terms: Additive manufacturing, Pore formation, Deep learning, Convolutional neural networks, High-throughput data, Imbalanced learning, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/f0eabfad36394d9dbc93e354f8730b5a

Matrix Linear Models for Connecting Metabolite Composition to Individual Characteristics

Authors: Gregory Farage, Chenhao Zhao, Hyo Young Choi, Timothy J. Garrett, Marshall B. Elam, Katerina Kechris, Śaunak Sen

Source: Metabolites, Vol 15, Iss 2, p 140 (2025)

Subject Terms: high-throughput data, metabolomics, lipidomics, bilinear models, Julia language, Microbiology, QR1-502

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Relation: https://www.mdpi.com/2218-1989/15/2/140; https://doaj.org/toc/2218-1989

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Volcano Routing: A Multi-Pipe High-Throughput Routing Protocol with Hole Avoidance for Multi-Beam Directional Mesh Networks

Authors: Toorchi, N., Hu, F., Pudlewski, S., Bentley, E., Kumar, S.

Source: IEEE Transactions on Mobile Computing IEEE Trans. on Mobile Comput. Mobile Computing, IEEE Transactions on. 19(12):2981-2996 Dec, 2020

Predicting Essential Proteins by Integrating Network Topology, Subcellular Localization Information, Gene Expression Profile and GO Annotation Data

Authors: Zhang, W., Xu, J., Zou, X.

Source: IEEE/ACM Transactions on Computational Biology and Bioinformatics IEEE/ACM Trans. Comput. Biol. and Bioinf. Computational Biology and Bioinformatics, IEEE/ACM Transactions on. 17(6):2053-2061 Jan, 2020

Molecular landscape of kidney allograft tissues data integration portal (NephroDIP): a curated database to improve integration of high-throughput kidney transplant datasets

Authors: Alex Boshart, Stefan Petrovic, Mark Abovsky, Chiara Pastrello, Sofia Farkona, Kieran Manion, Slaghaniya Neupane, Maya Allen, Igor Jurisica, Ana Konvalinka

Source: Frontiers in Immunology, Vol 15 (2024)

Subject Terms: data integration, integrative computational biology, kidney transplantation, high-throughput data, antibody-mediated rejection, interstitial fibrosis and tubular atrophy, Immunologic diseases. Allergy, RC581-607

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Relation: https://www.frontiersin.org/articles/10.3389/fimmu.2024.1469500/full; https://doaj.org/toc/1664-3224

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'R' U ready?: a case study using R to analyze changes in gene expression during evolution

Authors: Amy E. Pomeroy, Andrea Bixler, Stefanie H. Chen, Jennifer E. Kerr, Todd D. Levine, Elizabeth F. Ryder

Source: Frontiers in Education, Vol 9 (2024)

Subject Terms: high-throughput data analysis, R programming, case studies, evolutionary biology, data cleaning, data visualization, Education (General), L7-991

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/feduc.2024.1379910/full; https://doaj.org/toc/2504-284X

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Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies

Authors: María Alejandra González-González, Silvia V. Conde, Ramon Latorre, Stéphanie C. Thébault, Marta Pratelli, Nicholas C. Spitzer, Alexei Verkhratsky, Marie-Ève Tremblay, Cuneyt G. Akcora, Ana G. Hernández-Reynoso, Melanie Ecker, Jayme Coates, Kathleen L. Vincent, Brandy Ma

Source: Frontiers in Integrative Neuroscience, Vol 18 (2024)

Subject Terms: bioelectronic medicine, neuromodulation, channel biophysics, glia, neuronal plasticity, high throughput data, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429

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Relation: https://www.frontiersin.org/articles/10.3389/fnint.2024.1321872/full; https://doaj.org/toc/1662-5145

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L21-iPaD: An efficient method for drug-pathway association pairs inference

Authors: Dong-Qin Wang, Chun-Hou Zheng, Ying-Lian Gao, Jin-Xing Liu, Sha-Sha Wu, Jun-Liang Shang

Source: 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Bioinformatics and Biomedicine (BIBM), 2016 IEEE International Conference on. :664-669 Dec, 2016

Relation: 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

NEPTUNE: Real Time Stream Processing for Internet of Things and Sensing Environments

Authors: Buddhika, Thilina, Pallickara, Shrideep

Source: 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS) Parallel and Distributed Processing Symposium, 2016 IEEE International. :1143-1152 May, 2016

Relation: 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)

Identification of dysregulated miRNAs and their roles in breast cancer; An in silico meta‐analysis study

Authors: Davood Ghavi Dorabad, Zahra Foruzandeh, Zahra Torki, Amir Ebrahimi, Solmaz Hashemi, Mohammad Reza Alivand

Source: Informatics in Medicine Unlocked, Vol 44, Iss , Pp 101434- (2024)

Subject Terms: Breast cancer, Microarray GEO dataset, High-throughput data, Bioinformatic, In silico meta-analysis, miR-142-3p, Computer applications to medicine. Medical informatics, R858-859.7

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Relation: http://www.sciencedirect.com/science/article/pii/S2352914823002800; https://doaj.org/toc/2352-9148

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Computational modelling of immunological mechanisms: From statistical approaches to interpretable machine learning

Authors: María Rodríguez Martínez, Matteo Barberis, Anna Niarakis

Source: ImmunoInformatics, Vol 12, Iss , Pp 100029- (2023)

Subject Terms: Interpretable machine learning, Immunological mechanisms, Computational modelling, High-throughput data analysis, Statistical models, Computer applications to medicine. Medical informatics, R858-859.7

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2667119023000095; https://doaj.org/toc/2667-1190

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Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types

Authors: Jia Feng, Kailan Yang, Xuexue Liu, Min Song, Ping Zhan, Mi Zhang, Jinsong Chen, Jinbo Liu

Source: PeerJ, Vol 11, p e16304 (2023)

Subject Terms: Machine learning, Cancer microbiomics, Host-microbe interaction, High-throughput data, Medicine, Biology (General), QH301-705.5

File Description: electronic resource

Relation: https://peerj.com/articles/16304.pdf; https://peerj.com/articles/16304/; https://doaj.org/toc/2167-8359

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Incorporating feature reliability in false discovery rateestimation improves statistical power to detect differentially expressed features

Authors: Chong, Elizabeth, Huang, Yijian, Wu, Hao, Yu, Tianwei, Ghasemzadeh, Nima, Uppal, Karan, Quyyumi, Arshed A., Jones, Dean P.

Source: 2014 8th International Conference on Systems Biology (ISB) Systems Biology (ISB), 2014 8th International Conference on. :169-175 Oct, 2014

Relation: 2014 8th International Conference on Systems Biology (ISB)

First principles data-driven potentials for prediction of iron carbide clusters

Authors: Enhu Diao, Yurong He, Xuhong Liu, Qiang Tong, Tao Yang, Xiaotong Liu, James P. Lewis

Source: Frontiers in Quantum Science and Technology, Vol 2 (2023)

Subject Terms: iron carbide clusters, machine learning potentials, adsorbate prediction, cluster optimization, high-throughput data analysis, Technology

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/frqst.2023.1190522/full; https://doaj.org/toc/2813-2181

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Enhancement of the ASDEX Upgrade Real-Time Plasma Position Reflectometry Diagnostic

Authors: Santos, J. M., Santos, G. S., Zilker, M., Guimarais, L., Rapson, C., Treutterer, W., Goncalves, B.

Source: IEEE Transactions on Nuclear Science IEEE Trans. Nucl. Sci. Nuclear Science, IEEE Transactions on. 62(3):1195-1200 Jun, 2015

Prognosis prediction ability and prospective biological mechanisms of WDHD1 in hepatocellular carcinoma tissues

Authors: Rong-Quan He, Jian-Di Li, Wei-Ying He, Gang Chen, Zhi-Guang Huang, Ming-Fen Li, Wei-Zi Wu, Ji-Tian Chen, Yan-Qing Pan, Huan Jiang, Yi-Wu Dang, Li-Hua Yang

Source: Electronic Journal of Biotechnology, Vol 55, Iss , Pp 78-90 (2022)

Subject Terms: Chromatin immunoprecipitation sequencing, Complex pathogenesis immunohistochemistry, Gene microarrays, Hepatocellular carcinoma, High-throughput data, High-throughput sequencing, Biotechnology, TP248.13-248.65, Biology (General), QH301-705.5

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0717345821000579; https://doaj.org/toc/0717-3458

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Type 2 diabetes, gut microbiome, and systems biology: A novel perspective for a new era

Authors: Yoscelina Estrella Martínez-López, Diego A. Esquivel-Hernández, Jean Paul Sánchez-Castañeda, Daniel Neri-Rosario, Rodolfo Guardado-Mendoza, Osbaldo Resendis-Antonio

Source: Gut Microbes, Vol 14, Iss 1 (2022)

Subject Terms: Gut microbiome, type 2 diabetes, diet, physical activity, anti-diabetic drugs, high-throughput data, Diseases of the digestive system. Gastroenterology, RC799-869

File Description: electronic resource

Relation: https://doaj.org/toc/1949-0976; https://doaj.org/toc/1949-0984

Access URL: https://doaj.org/article/9c5d4bf9a0df4e7f887f9b16fecbc7d8

Molecular Mechanisms of Endometriosis Revealed Using Omics Data

Authors: Seong Beom Cho

Source: Biomedicines, Vol 11, Iss 8, p 2210 (2023)

Subject Terms: endometriosis, high-throughput data, disease gene, gene ontology, biological pathway, Biology (General), QH301-705.5

File Description: electronic resource

Relation: https://www.mdpi.com/2227-9059/11/8/2210; https://doaj.org/toc/2227-9059

Access URL: https://doaj.org/article/b53db332e5444025ae1275ddf668d286

Identification of hub genes and its correlation with the prognosis of acute myeloid leukemia based on high‐throughput data analysis

Authors: Wei Fu, Guo‐bin Cheng, Yao Ding, Ya‐jie Deng, Peng‐xiang Guo

Source: Precision Radiation Oncology, Vol 4, Iss 2, Pp 49-56 (2020)

Subject Terms: acute myeloid leukemia, high‐throughput data, hub genes, prognosis, Medical physics. Medical radiology. Nuclear medicine, R895-920, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282

File Description: electronic resource

Relation: https://doaj.org/toc/2398-7324

Access URL: https://doaj.org/article/446e5d7d94c74b8aa33c1dd2dacff666