Pub Date : 2024-07-11DOI: 10.1007/978-981-97-5128-0_6
Shuailin Xue, Fangfang Zhu, Changmiao Wang, Wenwen Min
{"title":"stEnTrans: Transformer-Based Deep Learning for Spatial Transcriptomics Enhancement","authors":"Shuailin Xue, Fangfang Zhu, Changmiao Wang, Wenwen Min","doi":"10.1007/978-981-97-5128-0_6","DOIUrl":"https://doi.org/10.1007/978-981-97-5128-0_6","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"63 3","pages":"63-75"},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141834741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-15DOI: 10.48550/arXiv.2308.01920
Usama Sardar, Sarwan Ali, Muhammad Sohaib Ayub, Muhammad Shoaib, Khurram Bashir, Imdadullah Khan, Murray Patterson
Nanobodies (Nb) are monomeric heavy-chain fragments derived from heavy-chain only antibodies naturally found in Camelids and Sharks. Their considerably small size (~3-4 nm; 13 kDa) and favorable biophysical properties make them attractive targets for recombinant production. Furthermore, their unique ability to bind selectively to specific antigens, such as toxins, chemicals, bacteria, and viruses, makes them powerful tools in cell biology, structural biology, medical diagnostics, and future therapeutic agents in treating cancer and other serious illnesses. However, a critical challenge in nanobodies production is the unavailability of nanobodies for a majority of antigens. Although some computational methods have been proposed to screen potential nanobodies for given target antigens, their practical application is highly restricted due to their reliance on 3D structures. Moreover, predicting nanobodyantigen interactions (binding) is a time-consuming and labor-intensive task. This study aims to develop a machine-learning method to predict Nanobody-Antigen binding solely based on the sequence data. We curated a comprehensive dataset of Nanobody-Antigen binding and nonbinding data and devised an embedding method based on gapped k-mers to predict binding based only on sequences of nanobody and antigen. Our approach achieves up to 90% accuracy in binding prediction and is significantly more efficient compared to the widely-used computational docking technique.
{"title":"Sequence-Based Nanobody-Antigen Binding Prediction","authors":"Usama Sardar, Sarwan Ali, Muhammad Sohaib Ayub, Muhammad Shoaib, Khurram Bashir, Imdadullah Khan, Murray Patterson","doi":"10.48550/arXiv.2308.01920","DOIUrl":"https://doi.org/10.48550/arXiv.2308.01920","url":null,"abstract":"Nanobodies (Nb) are monomeric heavy-chain fragments derived from heavy-chain only antibodies naturally found in Camelids and Sharks. Their considerably small size (~3-4 nm; 13 kDa) and favorable biophysical properties make them attractive targets for recombinant production. Furthermore, their unique ability to bind selectively to specific antigens, such as toxins, chemicals, bacteria, and viruses, makes them powerful tools in cell biology, structural biology, medical diagnostics, and future therapeutic agents in treating cancer and other serious illnesses. However, a critical challenge in nanobodies production is the unavailability of nanobodies for a majority of antigens. Although some computational methods have been proposed to screen potential nanobodies for given target antigens, their practical application is highly restricted due to their reliance on 3D structures. Moreover, predicting nanobodyantigen interactions (binding) is a time-consuming and labor-intensive task. This study aims to develop a machine-learning method to predict Nanobody-Antigen binding solely based on the sequence data. We curated a comprehensive dataset of Nanobody-Antigen binding and nonbinding data and devised an embedding method based on gapped k-mers to predict binding based only on sequences of nanobody and antigen. Our approach achieves up to 90% accuracy in binding prediction and is significantly more efficient compared to the widely-used computational docking technique.","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124854678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-07DOI: 10.1007/978-3-030-91415-8_14
Sarwan Ali, Bikram Sahoo, N. Ullah, Alexander Zelikovskiy, M. Patterson, Imdadullah Khan
{"title":"A k-mer Based Approach for SARS-CoV-2 Variant Identification","authors":"Sarwan Ali, Bikram Sahoo, N. Ullah, Alexander Zelikovskiy, M. Patterson, Imdadullah Khan","doi":"10.1007/978-3-030-91415-8_14","DOIUrl":"https://doi.org/10.1007/978-3-030-91415-8_14","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125021035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1007/978-3-030-57821-3_24
Selcen Ari Yuka, Alper Yilmaz
{"title":"A New Network-Based Tool to Analyse Competing Endogenous RNAs","authors":"Selcen Ari Yuka, Alper Yilmaz","doi":"10.1007/978-3-030-57821-3_24","DOIUrl":"https://doi.org/10.1007/978-3-030-57821-3_24","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115646021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1007/978-3-030-57821-3_32
F. Rondel, A. Hosseini, Bikram Sahoo, S. Knyazev, Igor Mandric, F. Stewart, I. Măndoiu, B. Pasaniuc, A. Zelikovsky
{"title":"Estimating Enzyme Participation in Metabolic Pathways for Microbial Communities from RNA-seq Data","authors":"F. Rondel, A. Hosseini, Bikram Sahoo, S. Knyazev, Igor Mandric, F. Stewart, I. Măndoiu, B. Pasaniuc, A. Zelikovsky","doi":"10.1007/978-3-030-57821-3_32","DOIUrl":"https://doi.org/10.1007/978-3-030-57821-3_32","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125493207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1007/978-3-030-57821-3_30
Yangxiao Wang, Wooyoung Kim
{"title":"Identification of Essential Genes with NemoProfile and Various Machine Learning Models","authors":"Yangxiao Wang, Wooyoung Kim","doi":"10.1007/978-3-030-57821-3_30","DOIUrl":"https://doi.org/10.1007/978-3-030-57821-3_30","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128526453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1007/978-3-030-57821-3_37
Nikolai S. Bykov, Olga M. Sigalova, M. Gelfand, Aleksandra Galitsyna
{"title":"HiChew: a Tool for TAD Clustering in Embryogenesis","authors":"Nikolai S. Bykov, Olga M. Sigalova, M. Gelfand, Aleksandra Galitsyna","doi":"10.1007/978-3-030-57821-3_37","DOIUrl":"https://doi.org/10.1007/978-3-030-57821-3_37","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124188997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Diagnosis of ASD from rs-fMRI Images Based on Brain Dynamic Networks","authors":"Hongyu Guo, Wutao Yin, Sakib Mostafa, Fang-Xiang Wu","doi":"10.1007/978-3-030-57821-3_15","DOIUrl":"https://doi.org/10.1007/978-3-030-57821-3_15","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"306 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121281225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1007/978-3-030-57821-3_9
Nian Wang, Min Zeng, Jiashuai Zhang, Yiming Li, Min Li
{"title":"Ess-NEXG: Predict Essential Proteins by Constructing a Weighted Protein Interaction Network Based on Node Embedding and XGBoost","authors":"Nian Wang, Min Zeng, Jiashuai Zhang, Yiming Li, Min Li","doi":"10.1007/978-3-030-57821-3_9","DOIUrl":"https://doi.org/10.1007/978-3-030-57821-3_9","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114805538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.1007/978-3-030-57821-3_35
Xingfeng Lv, Jinbao Li, Qin Yan
{"title":"Automated Detection of Sleep Apnea from Abdominal Respiratory Signal Using Hilbert-Huang Transform","authors":"Xingfeng Lv, Jinbao Li, Qin Yan","doi":"10.1007/978-3-030-57821-3_35","DOIUrl":"https://doi.org/10.1007/978-3-030-57821-3_35","url":null,"abstract":"","PeriodicalId":354035,"journal":{"name":"International Symposium on Bioinformatics Research and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134207153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：