{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T21:44:50Z","timestamp":1777931090114,"version":"3.51.4"},"reference-count":69,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T00:00:00Z","timestamp":1772841600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62501110.2"],"award-info":[{"award-number":["62501110.2"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62501110"],"award-info":[{"award-number":["62501110"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020TQ0138"],"award-info":[{"award-number":["2020TQ0138"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Ecological Informatics"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.ecoinf.2026.103696","type":"journal-article","created":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T17:52:37Z","timestamp":1773942757000},"page":"103696","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["DeepPFT-GANCap: An explainable attention-based hybrid deep learning framework integrating protein language models and wavelet denoising-based evolutionary features for photosystem-II core protein prediction"],"prefix":"10.1016","volume":"95","author":[{"given":"Wajdi","family":"Alghamdi","sequence":"first","affiliation":[]},{"given":"Farman","family":"Ali","sequence":"additional","affiliation":[]},{"given":"Abdulmohsen","family":"Algarni","sequence":"additional","affiliation":[]},{"given":"Omar","family":"Alghushairy","sequence":"additional","affiliation":[]},{"given":"Majdi","family":"Khalid","sequence":"additional","affiliation":[]},{"given":"Meng-Ze","family":"Du","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0005","doi-asserted-by":"crossref","first-page":"33676","DOI":"10.1038\/s41598-025-18518-5","article-title":"A deep learning model for epidermal growth factor receptor prediction using ensemble residual convolutional neural network","volume":"15","author":"Alghamdi","year":"2025","journal-title":"Sci. Rep."},{"issue":"22","key":"10.1016\/j.ecoinf.2026.103696_bb0010","doi-asserted-by":"crossref","first-page":"12330","DOI":"10.1080\/07391102.2023.2269280","article-title":"Machine learning-based model for accurate identification of druggable proteins using light extreme gradient boosting","volume":"42","author":"Alghushairy","year":"2024","journal-title":"J. Biomol. Struct. Dyn."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0015","doi-asserted-by":"crossref","first-page":"104639","DOI":"10.1016\/j.chemolab.2022.104639","article-title":"DBP-DeepCNN: prediction of DNA-binding proteins using wavelet-based denoising and deep learning","author":"Ali","year":"2022","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0020","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.jtbi.2015.07.034","article-title":"Classification of membrane protein types using voting feature interval in combination with Chou' s pseudo amino acid composition","volume":"384","author":"Ali","year":"2015","journal-title":"J. Theor. Biol."},{"issue":"7","key":"10.1016\/j.ecoinf.2026.103696_bb0025","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1007\/s10822-019-00207-x","article-title":"DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information","volume":"33","author":"Ali","year":"2019","journal-title":"J. Comput. Aided Mol. Des."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.ab.2019.113494","article-title":"SDBP-pred: prediction of single-stranded and double-stranded DNA-binding proteins by extending consensus sequence and K-segmentation strategies into PSSM","volume":"589","author":"Ali","year":"2020","journal-title":"Anal. Biochem."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2022.105533","article-title":"Target-DBPPred: an intelligent model for prediction of DNA-binding proteins using discrete wavelet transform based compression and light eXtreme gradient boosting","volume":"145","author":"Ali","year":"2022","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijbiomac.2023.125296","article-title":"Deep-AGP: prediction of angiogenic protein by integrating two-dimensional convolutional neural network with discrete cosine transform","volume":"243","author":"Ali","year":"2023","journal-title":"Int. J. Biol. Macromol."},{"issue":"7","key":"10.1016\/j.ecoinf.2026.103696_bb0045","doi-asserted-by":"crossref","first-page":"4033","DOI":"10.1007\/s11831-023-09933-w","article-title":"Recent advances in machine learning-based models for prediction of antiviral peptides","volume":"30","author":"Ali","year":"2023","journal-title":"Arch. Comput. Meth. Eng."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0050","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.ymeth.2024.04.004","article-title":"DEEP-EP: identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery","volume":"226","author":"Ali","year":"2024","journal-title":"Methods"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.jocs.2024.102388","article-title":"IP-GCN: a deep learning model for prediction of insulin using graph convolutional network for diabetes drug design","volume":"81","author":"Ali","year":"2024","journal-title":"J. Comput. Sci."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.jocs.2024.102448","article-title":"VEGF-ERCNN: a deep learning-based model for prediction of vascular endothelial growth factor using ensemble residual CNN","volume":"83","author":"Ali","year":"2024","journal-title":"J. Comput. Sci."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2025.103400","article-title":"Deep-cabpred: deep learning model for predicting functional chlorophyll ab binding proteins in trait-based plant ecology using hybrid embedding with semi-normalized temporal convolutional networks","author":"Ali","year":"2025","journal-title":"Ecol. Inform."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0070","first-page":"1","article-title":"Comprehensive analysis of computational models for prediction of anticancer peptides using machine learning and deep learning","author":"Ali","year":"2025","journal-title":"Arch. Comput. Methods Eng."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijbiomac.2025.148336","article-title":"Identification of defensins using transformer-derived protein embeddings and discrete cosine transformation-enhanced evolutionary features with generative adversarial capsule bidirectional temporal convolutional neural network","author":"Ali","year":"2025","journal-title":"Int. J. Biol. Macromol."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0080","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1007\/s13755-025-00347-5","article-title":"Leveraging deep learning for epigenetic protein prediction: a novel approach for early lung cancer diagnosis and drug discovery","volume":"13","author":"Ali","year":"2025","journal-title":"Health Informa. Sci. Syst."},{"issue":"12","key":"10.1016\/j.ecoinf.2026.103696_bb0085","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.1038\/s41592-019-0598-1","article-title":"Unified rational protein engineering with sequence-based deep representation learning","volume":"16","author":"Alley","year":"2019","journal-title":"Nat. Methods"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.rineng.2024.103348","article-title":"Multi-headed ensemble residual CNN: a powerful tool for fibroblast growth factor prediction","volume":"24","author":"Almusallam","year":"2024","journal-title":"Results Eng."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0095","first-page":"1","article-title":"Deep-VEGF: deep stacked ensemble model for prediction of vascular endothelial growth factor by concatenating gated recurrent unit with two-dimensional convolutional neural network","author":"Alsini","year":"2024","journal-title":"J. Biomol. Struct. Dyn."},{"issue":"2","key":"10.1016\/j.ecoinf.2026.103696_bb0100","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/0005-2728(93)90134-2","article-title":"Photoinhibition of photosystem II. Inactivation, protein damage and turnover","volume":"1143","author":"Aro","year":"1993","journal-title":"Biochimica et Biophysica Acta (BBA)-Bioenergetics"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0105","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.3389\/fmicb.2019.01315","article-title":"Proteomic de-regulation in cyanobacteria in response to abiotic stresses","volume":"10","author":"Babele","year":"2019","journal-title":"Front. Microbiol."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.chemolab.2022.104697","article-title":"iDBP-PBMD: a machine learning model for detection of DNA-binding proteins by extending compression techniques into evolutionary profile","volume":"231","author":"Banjar","year":"2022","journal-title":"Chemom. Intell. Lab. Syst."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0115","article-title":"Phage_UniR_LGBM: phage virion proteins classification with UniRep features and LightGBM model","volume":"2022","author":"Bao","year":"2022","journal-title":"Comput. Math. Methods Med."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0120","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1017\/S0033583502003839","article-title":"Photosystem II: the engine of life","volume":"36","author":"Barber","year":"2003","journal-title":"Q. Rev. Biophys."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0125","doi-asserted-by":"crossref","first-page":"2150018","DOI":"10.1142\/S0219720021500189","article-title":"DBP-GAPred: an intelligent method for prediction of DNA-binding proteins types by enhanced evolutionary profile features with ensemble learning","author":"Barukab","year":"2021","journal-title":"J. Bioinforma. Comput. Biol."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0130","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.116729","article-title":"DBP-CNN: deep learning-based prediction of DNA-binding proteins by coupling discrete cosine transform with two-dimensional convolutional neural network","author":"Barukab","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0135","article-title":"Framework for deep learning diagnosis of plant disorders in horticultural crops: from data collection tools to user-friendly web and mobile apps","volume":"84","author":"Buchaillot","year":"2024","journal-title":"Eco. Inform."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.infsof.2023.107166","article-title":"A novel detection model for abnormal network traffic based on bidirectional temporal convolutional network","volume":"157","author":"Chen","year":"2023","journal-title":"Inf. Softw. Technol."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0145","article-title":"Mixture of decoupled message passing experts with entropy constraint for general node classification","author":"Chen","year":"2025","journal-title":"arXiv preprint"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0150","series-title":"Proceedings of the 28th ACM International Conference on Multimedia","article-title":"Sequential attention GAN for interactive image editing","author":"Cheng","year":"2020"},{"issue":"10","key":"10.1016\/j.ecoinf.2026.103696_bb0155","doi-asserted-by":"crossref","first-page":"4310","DOI":"10.1021\/acs.jcim.3c02061","article-title":"Predicting antimicrobial peptides using ESMFold-predicted structures and ESM-2-based amino acid features with graph deep learning","volume":"64","author":"Cordoves-Delgado","year":"2024","journal-title":"J. Chem. Inf. Model."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0160","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1186\/s12951-021-01081-2","article-title":"Advances and insights in the diagnosis of viral infections","volume":"19","author":"Dronina","year":"2021","journal-title":"J. Nanobiotechnol."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0165","doi-asserted-by":"crossref","first-page":"7112","DOI":"10.1109\/TPAMI.2021.3095381","article-title":"ProtTrans: towards cracking the language of life's code through self-supervised learning","volume":"44","author":"Elnaggar","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103696_bb0170","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1110\/ps.8.5.978","article-title":"ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites","volume":"8","author":"Emanuelsson","year":"1999","journal-title":"Protein Sci."},{"issue":"4","key":"10.1016\/j.ecoinf.2026.103696_bb0175","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1038\/nprot.2007.131","article-title":"Locating proteins in the cell using TargetP, SignalP and related tools","volume":"2","author":"Emanuelsson","year":"2007","journal-title":"Nat. Protoc."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0180","article-title":"Fast genomic analysis of aquatic bird populations from short single-end reads considering sex-related pitfalls","volume":"56","author":"Faux","year":"2020","journal-title":"Eco. Inform."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0185","doi-asserted-by":"crossref","first-page":"54","DOI":"10.21015\/vtcs.v11i1.1396","article-title":"DeepImmuno-PSSM: identification of immunoglobulin based on deep learning and PSSM-profiles","volume":"11","author":"Ghulam","year":"2023","journal-title":"VAWKUM Transact. Comp. Sci."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0190","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1186\/s12859-019-3220-8","article-title":"Modeling aspects of the language of life through transfer-learning protein sequences","volume":"20","author":"Heinzinger","year":"2019","journal-title":"BMC Bioinforma."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0195","doi-asserted-by":"crossref","DOI":"10.1093\/bioadv\/vbae119","article-title":"In the twilight zone of protein sequence homology: do protein language models learn protein structure?","volume":"4","author":"Kabir","year":"2024","journal-title":"Bioinformatics Adv."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0200","first-page":"1","article-title":"An ensemble computational model for prediction of clathrin protein by coupling machine learning with discrete cosine transform","author":"Khalid","year":"2024","journal-title":"J. Biomol. Struct. Dyn."},{"issue":"14","key":"10.1016\/j.ecoinf.2026.103696_bb0205","doi-asserted-by":"crossref","first-page":"7247","DOI":"10.1080\/07391102.2024.2329777","article-title":"An ensemble computational model for prediction of clathrin protein by coupling machine learning with discrete cosine transform","volume":"43","author":"Khalid","year":"2025","journal-title":"J. Biomol. Struct. Dyn."},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103696_bb0210","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11704-020-9504-3","article-title":"PiEnPred: a bi-layered discriminative model for enhancers and their subtypes via novel cascade multi-level subset feature selection algorithm","volume":"15","author":"Khan","year":"2021","journal-title":"Front. Comput. Sci."},{"issue":"3","key":"10.1016\/j.ecoinf.2026.103696_bb0215","doi-asserted-by":"crossref","first-page":"826","DOI":"10.1021\/acs.jcim.2c01417","article-title":"AFP-SPTS: an accurate prediction of antifreeze proteins using sequential and pseudo-tri-slicing evolutionary features with an extremely randomized tree","volume":"63","author":"Khan","year":"2023","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.chemolab.2022.104729","article-title":"Comparative analysis of the existing methods for prediction of antifreeze proteins","volume":"232","author":"Khan","year":"2023","journal-title":"Chemom. Intell. Lab. Syst."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0225","first-page":"31","article-title":"The discrete cosine transform (DCT): theory and application","volume":"114","author":"Khayam","year":"2003","journal-title":"Michigan State University"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0230","doi-asserted-by":"crossref","DOI":"10.1109\/TBDATA.2025.3588080","article-title":"GTPool: graph transformer pooling with diverse sampling","author":"Li","year":"2025","journal-title":"IEEE Trans. Big Data"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0235","article-title":"DAM-GT: dual positional encoding-based attention masking graph transformer for node classification","author":"Li","year":"2025","journal-title":"arXiv preprint"},{"issue":"6637","key":"10.1016\/j.ecoinf.2026.103696_bb0240","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1126\/science.ade2574","article-title":"Evolutionary-scale prediction of atomic-level protein structure with a language model","volume":"379","author":"Lin","year":"2023","journal-title":"Science"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0245","article-title":"Identification of plant species in an alpine steppe of northern Tibet using close-range hyperspectral imagery","volume":"61","author":"Liu","year":"2021","journal-title":"Eco. Inform."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0250","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13593-014-0246-1","article-title":"Advanced methods of plant disease detection. A review","volume":"35","author":"Martinelli","year":"2015","journal-title":"Agron. Sustain. Dev."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0255","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2016.01419","article-title":"Using deep learning for image-based plant disease detection","volume":"7","author":"Mohanty","year":"2016","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0260","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.ecoinf.2018.09.007","article-title":"A deep learning method for accurate and fast identification of coral reef fishes in underwater images","volume":"48","author":"Mouillot","year":"2018","journal-title":"Ecol. Inform."},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103696_bb0265","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.bbabio.2006.11.019","article-title":"Photoinhibition of photosystem II under environmental stress","volume":"1767","author":"Murata","year":"2007","journal-title":"Biochimica et Biophysica Acta (BBA)-Bioenergetics"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0270","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1146\/annurev-biochem-092914-041942","article-title":"Structure and energy transfer in photosystems of oxygenic photosynthesis","volume":"84","author":"Nelson","year":"2015","journal-title":"Annu. Rev. Biochem."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0275","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/aob\/mcq059","article-title":"Recent advances in understanding the assembly and repair of photosystem II","volume":"106","author":"Nixon","year":"2010","journal-title":"Ann. Bot."},{"issue":"D1","key":"10.1016\/j.ecoinf.2026.103696_bb0280","doi-asserted-by":"crossref","first-page":"D480","DOI":"10.1093\/nar\/gkaa1100","volume":"49","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0285","series-title":"2020 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)","article-title":"Machine learning based plant diseases detection: a review","author":"Pardede","year":"2020"},{"issue":"140","key":"10.1016\/j.ecoinf.2026.103696_bb0290","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"J. Mach. Learn. Res."},{"issue":"2","key":"10.1016\/j.ecoinf.2026.103696_bb0295","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1111\/1365-2745.12211","article-title":"The world-wide \u2018fast\u2013slow'plant economics spectrum: a traits manifesto","volume":"102","author":"Reich","year":"2014","journal-title":"J. Ecol."},{"issue":"15","key":"10.1016\/j.ecoinf.2026.103696_bb0300","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2016239118","article-title":"Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences","volume":"118","author":"Rives","year":"2021","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0305","article-title":"Tgformer: a graph transformer framework for knowledge graph embedding","author":"Shi","year":"2024","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0310","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-022-09484-3","article-title":"XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set","volume":"12","author":"Sikander","year":"2022","journal-title":"Sci. Rep."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103696_bb0315","doi-asserted-by":"crossref","first-page":"33","DOI":"10.70003\/160792642026012701004","article-title":"Overview of capsule neural networks","volume":"23","author":"Sun","year":"2022","journal-title":"J. Internet Technol."},{"key":"10.1016\/j.ecoinf.2026.103696_bb0320","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.compmedimag.2019.05.001","article-title":"Brain tumor classification for MR images using transfer learning and fine-tuning","volume":"75","author":"Swati","year":"2019","journal-title":"Comput. Med. Imaging Graph."},{"issue":"4","key":"10.1016\/j.ecoinf.2026.103696_bb0325","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.tplants.2008.01.005","article-title":"How do environmental stresses accelerate photoinhibition?","volume":"13","author":"Takahashi","year":"2008","journal-title":"Trends Plant Sci."},{"issue":"7345","key":"10.1016\/j.ecoinf.2026.103696_bb0330","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/nature09913","article-title":"Crystal structure of oxygen-evolving photosystem II at a resolution of 1.9 \u00c5","volume":"473","author":"Umena","year":"2011","journal-title":"Nature"},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103696_bb0335","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1111\/j.0030-1299.2007.15559.x","article-title":"Let the concept of trait be functional!","volume":"116","author":"Violle","year":"2007","journal-title":"Oikos"},{"key":"10.1016\/j.ecoinf.2026.103696_bb0340","series-title":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","article-title":"Efficient nodes representation learning with residual feature propagation","author":"Wu","year":"2021"},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103696_bb0345","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1049\/syb2.12108","article-title":"Deep-GB: a novel deep learning model for globular protein prediction using CNN-BiLSTM architecture and enhanced PSSM with trisection strategy","volume":"18","author":"Zouari","year":"2024","journal-title":"IET Syst. Biol."}],"container-title":["Ecological Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1574954126001020?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1574954126001020?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T00:34:35Z","timestamp":1777682075000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1574954126001020"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":69,"alternative-id":["S1574954126001020"],"URL":"https:\/\/doi.org\/10.1016\/j.ecoinf.2026.103696","relation":{},"ISSN":["1574-9541"],"issn-type":[{"value":"1574-9541","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DeepPFT-GANCap: An explainable attention-based hybrid deep learning framework integrating protein language models and wavelet denoising-based evolutionary features for photosystem-II core protein prediction","name":"articletitle","label":"Article Title"},{"value":"Ecological Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ecoinf.2026.103696","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"103696"}}