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ORCID13th BCB 2022: Northbrook, IL, USA
- BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7 - 10, 2022. ACM 2022, ISBN 978-1-4503-9386-7
Sequence analysis
- Amine M. Remita
, Abdoulaye Baniré Diallo:
EvoVGM: a deep variational generative model for evolutionary parameter estimation. 1:1-1:10 - Utkrisht Rajkumar, Sara Javadzadeh, Mihir Bafna, Dongxia Wu, Rose Yu, Jingbo Shang, Vineet Bafna:
DeepViFi: detecting oncoviral infections in cancer genomes using transformers. 2:1-2:8 - Ziqi Ke, Haris Vikalo:
Deep learning for assembly of haplotypes and viral quasispecies from short and long sequencing reads. 3:1-3:10 - Huey-Eng Chua, Lisa Tucker-Kellogg, Sourav S. Bhowmick:
ArcheGEO: towards improving relevance of gene expression omnibus search results. 4:1-4:10 - Weizhi An, Yuzhi Guo, Yatao Bian, Hehuan Ma, Jinyu Yang, Chunyuan Li, Junzhou Huang:
MoDNA: motif-oriented pre-training for DNA language model. 5:1-5:5
Electronic health records
- Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating health disparities in EHR via deconfounder. 6:1-6:6 - Yuqing Wang, Yun Zhao, Linda R. Petzold:
Predicting the need for blood transfusion in intensive care units with reinforcement learning. 7:1-7:10 - Sayantan Kumar, Sean C. Yu, Thomas George Kannampallil, Zachary B. Abrams, Andrew P. Michelson, Philip R. O. Payne:
Self-explaining neural network with concept-based explanations for ICU mortality prediction. 8:1-8:9 - Tingyi Wanyan, Mingquan Lin, Eyal Klang, Kartikeya M. Menon, Faris F. Gulamali, Ariful Azad, Yiye Zhang, Ying Ding, Zhangyang Wang, Fei Wang, Benjamin S. Glicksberg, Yifan Peng:
Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction. 9:1-9:9 - Ping Wang, Tian Shi, Khushbu Agarwal, Sutanay Choudhury, Chandan K. Reddy:
Attention-based aspect reasoning for knowledge base question answering on clinical notes. 10:1-10:6
Systems biology
- Mert Erden, Megan Gelement, Sarrah Hakimjee, Kyla Levin, Mary-Joy Sidhom, Kapil Devkota, Lenore J. Cowen:
Neighborhood embedding and re-ranking of disease genes with ADAGIO. 11:1-11:11 - Alisa Yurovsky, Justin Gardin, Bruce Futcher, Steven Skiena:
Statistical methodology for ribosomal frameshift detection. 12:1-12:10 - Van-Giang Trinh, Kunihiko Hiraishi, Belaid Benhamou:
Computing attractors of large-scale asynchronous boolean networks using minimal trap spaces. 13:1-13:10 - Blessing Kolawole, Lenore J. Cowen:
Combining spectral clustering and large cut algorithms to find compensatory functional modules from yeast physical and genetic interaction data with GLASS. 14:1-14:4 - Ashley Babjac, Taylor M. Royalty, Andrew D. Steen, Scott J. Emrich:
A comparison of dimensionality reduction methods for large biological data. 15:1-15:7
Health monitoring & phenotyping
- Yuxi Liu, Zhenhao Zhang, Antonio Jimeno-Yepes, Flora D. Salim:
Modeling long-term dependencies and short-term correlations in patient journey data with temporal attention networks for health prediction. 16:1-16:10 - Zongxing Xie, Hanrui Wang, Song Han, Elinor Schoenfeld, Fan Ye:
DeepVS: a deep learning approach for RF-based vital signs sensing. 17:1-17:5 - Eric V. Strobl, Thomas A. Lasko:
Identifying patient-specific root causes of disease. 18:1-18:10 - Ramin Ramazi, Mary Elizabeth Bowen, Rahmatollah Beheshti:
Predicting acute events using the movement patterns of older adults: an unsupervised clustering method. 19:1-19:9
Structural bioinformatics
- Avik Bhattacharya, Molly C. Lyons, Samuel J. Landry, Ramgopal R. Mettu:
Incorporating antigen processing into CD4+ T cell epitope prediction with integer linear programming. 20:1-20:10 - Mahdi Rahbar, Rahul Kumar Chauhan, Pankil Nimeshbhai Shah, Renzhi Cao, Dong Si, Jie Hou:
Deep graph learning to estimate protein model quality using structural constraints from multiple sequence alignments. 21:1-21:10 - Maor Turner, Mira Barshai, Yaron Orenstein:
rG4detector: convolutional neural network to predict RNA G-quadruplex propensity based on rG4-seq data. 22:1-22:9 - Andrew Hornback, Wenqi Shi, Felipe O. Giuste, Yuanda Zhu, Ashley M. Carpenter, Coleman Hilton, Vinieth N. Bijanki, Hiram Stahl, Gary S. Gottesman, Chad Purnell, Henry J. Iwinski, J. Michael Wattenbarger, May D. Wang:
Development of a generalizable multi-site and multi-modality clinical data cloud infrastructure for pediatric patient care. 23:1-23:10 - Adele P. Peskin, Joe Chalfoun, Michael Halter, Anne L. Plant:
Semi-supervised 3D neural networks to track iPS cell division in label-free phase contrast time series images. 24:1-24:7
Single cell omics
- Siyuan Shan, Vishal Athreya Baskaran, Haidong Yi, Jolene Ranek, Natalie Stanley, Junier B. Oliva:
Transparent single-cell set classification with kernel mean embeddings. 25:1-25:10 - Vishal Athreya Baskaran, Jolene Ranek, Siyuan Shan, Natalie Stanley, Junier B. Oliva:
Distribution-based sketching of single-cell samples. 26:1-26:10 - Honglin Wang, Pujan Joshi, Chenyu Zhang, Peter F. Maye, David W. Rowe, Dong-Guk Shin:
rCom: a route-based framework inferring cell type communication and regulatory network using single cell data. 27:1-27:4 - Haidong Yi, Natalie Stanley:
CytoEMD: detecting and visualizing between-sample variation in relation to phenotype with earth mover's distance. 28:1-28:14 - Sapan Bhandari, Nathan P. Whitener, Konghao Zhao, Natalia Khuri:
Multi-target integration and annotation of single-cell RNA-sequencing data. 29:1-29:4
Machine learning & drug design
- Tom Johnsten, Aishwarya Prakash, Grant T. Daly, Ryan G. Benton, Tristan Clark:
Computational framework for generating synthetic signal peptides. 30:1-30:7 - Aysegul Bumin, Anna M. Ritz, Donna K. Slonim, Tamer Kahveci, Kejun Huang:
FiT: fiber-based tensor completion for drug repurposing. 31:1-31:10 - Aisharjya Sarkar, Aaditya Singh, Richard Bailey, Alin Dobra, Tamer Kahveci:
Optimal separation of high dimensional transcriptome for complex multigenic traits. 32:1-32:5 - Sudha Tushara Sadasivuni, Yanqing Zhang:
Timestamp analysis of mental health tweets of Twitter users along with COVID-19 confirmed cases. 33:1-33:6 - Hehuan Ma, Feng Jiang, Yu Rong, Yuzhi Guo, Junzhou Huang:
Robust self-training strategy for various molecular biology prediction tasks. 34:1-34:5
Medical imaging
- Diego Machado Reyes, Mansu Kim, Hanqing Chao, Li Shen, Pingkun Yan:
Connectome transformer with anatomically inspired attention for Parkinson's diagnosis. 35:1-35:4 - Javier Pastorino, Ashis Kumer Biswas:
Data adequacy bias impact in a data-blinded semi-supervised GAN for privacy-aware COVID-19 chest X-ray classification. 36:1-36:8 - Jun Bai, Annie Jin, Andre Jin, Tianyu Wang, Clifford Yang, Sheida Nabavi:
Applying graph convolution neural network in digital breast tomosynthesis for cancer classification. 37:1-37:10 - Lillian Zhu, Feng Zhu, Jodi Price:
TopographyNET: a deep learning model for EEG-based mind wandering detection. 38:1-38:10
Graphs & networks
- Yuanfang Ren, Aisharjya Sarkar, Aysegul Bumin, Kejun Huang, Pierangelo Veltri, Alin Dobra, Tamer Kahveci:
Identification of co-existing embeddings of a motif in multilayer networks. 39:1-39:10 - Satyaki Roy, Preetam Ghosh:
Examining post-pandemic behaviors influencing human mobility trends. 40:1-40:10 - Anqi Wei, Liangjiang Wang:
Deep sequence representation learning for predicting human proteins with liquid-liquid phase separation propensity and synaptic functions. 41:1-41:8
COVID-19
- Nooriyan Poonawala-Lohani, Patricia Riddle, Mehnaz Adnan, Jörg Wicker:
Geographic ensembles of observations using randomised ensembles of autoregression chains: ensemble methods for spatio-temporal time series forecasting of influenza-like illness. 42:1-42:7 - Natalia Khuri, Sapan Bhandari, Esteban Murillo Burford, Nathan P. Whitener, Konghao Zhao:
An evolutionary approach to data valuation. 43:1-43:10 - Jun Bai, Bingjun Li, Sheida Nabavi:
Semi-supervised classification of disease prognosis using CR images with clinical data structured graph. 44:1-44:9 - Aekansh Goel, Zachary Mudge, Sarah Bi, Charles Brenner, Nicholas Huffman, Felipe O. Giuste, Benoit Marteau, Wenqi Shi, May D. Wang:
Identification of covid-19 severity and associated genetic biomarkers based on scrna-SEQ data. 45:1-45:5 - Yuanda Zhu, Aishwarya Mahale, Kourtney Peters, Lejy Mathew, Felipe O. Giuste, Blake J. Anderson, May D. Wang:
Using natural language processing on free-text clinical notes to identify patients with long-term COVID effects. 46:1-46:9
Clinical trials & outcome prediction
- Brendan E. Odigwe, Alireza Bagheri Rajeoni, Celestine I. Odigwe, Francis G. Spinale, Homayoun Valafar:
Application of machine learning for patient response prediction to cardiac resynchronization therapy. 47:1-47:4 - Li Zeng, Zhaolong Yu, Yiliang Zhang, Hongyu Zhao:
A general kernel boosting framework integrating pathways for predictive modeling based on genomic data. 48:1-48:8 - Zifeng Wang, Jimeng Sun:
SurvTRACE: transformers for survival analysis with competing events. 49:1-49:9 - Supratim Das, Xinghua Shi:
Offspring GAN augments biased human genomic data. 50:1-50:10
Genomic variation
- Neda Tavakoli, Daniel Gibney, Srinivas Aluru:
Haplotype-aware variant selection for genome graphs. 51:1-51:9 - Syed Fahad Sultan, Xingzhi Guo, Steven Skiena:
Low-dimensional genotype embeddings for predictive models. 52:1-52:4 - Meijun Gao, Wei Wang, Kevin J. Liu:
The impact of gene sequence alignment and gene tree estimation error on summary-based species network estimation. 53:1-53:17
Ontologies & databases
- Yuxuan Lu, Jingya Yan, Zhixuan Qi, Zhongzheng Ge, Yongping Du:
Contextual embedding and model weighting by fusing domain knowledge on biomedical question answering. 54:1-54:4 - Reza Mazloom, Leighton Pritchard, C. Titus Brown, Boris A. Vinatzer, Lenwood S. Heath:
LINgroups as a principled approach to compare and integrate multiple bacterial taxonomies. 55:1-55:7 - Suyeon Kim, Ishwor Thapa, Hesham Ali:
A multi-omics graph database for data integration and knowledge extraction. 56:1-56:6 - Hannah Guan, Chonghao Zhang:
Predicting diabetes in imbalanced datasets using neural networks. 57:1-57:10 - Rushank Goyal, Rashmi Chowdhary:
Antibiotic resistance prediction and biomarker discovery in Neisseria gonorrhoeae. 58:1 - Rushank Goyal:
A novel three-step transcriptomic framework for cancer prediction. 59:1 - Yana Hrytsenko, Noah M. Daniels, Rachel S. Schwartz:
Determining population structure from k-mer frequencies. 60:1 - Salvador Eugenio C. Caoili:
B-cell epitope prediction for antipeptide paratopes with the HAPTIC2/HEPTAD user toolkit (HUT). 61:1 - Maria Mannone, Veronica Distefano:
Trajectory-based and sound-based medical data clustering. 62:1 - Jingwen Zhang, Enze Xu, Minghan Chen:
AT[N]-net: multimodal spatiotemporal network for subtype identification in Alzheimer's disease. 63:1 - Huyen Trang Dang, Shi Jie Samuel Tan, Sara Mathieson:
Comparison of cohort-based identical-by-descent (IBD) segment finding methods for endogamous populations. 64:1 - Michael A. Zeller, Anugrah Saxena, Giovani Trevisan, Aditi Sharma, Daniel Linhares, Karen M. Krueger, Jianqiang Zhang, Phillip C. Gauger:
PRRSView: an analytical platform for the assessment of PRRSV ORF5 genetic sequences. 65:1 - Gangadhar Katuri, Epaminondas Rosa Jr., Rosangela Follmann:
Detecting synchronization in brain activity. 66:1 - Jhonatan Tavori, Hanoch Levy:
Greedy and speedy: optimal vaccination strategies in multi-region heterogeneous networks. 67:1 - Vinay Raj:
Analysis of impact of diabetes mellitus in Arkansas and U.S. 68:1 - Zheming Jin, Jeffrey S. Vetter:
Performance portability study of epistasis detection using SYCL on NVIDIA GPU. 69:1-69:8 - Maria Chiara Martinis, Chiara Zucco, Mario Cannataro:
An Italian lexicon-based sentiment analysis approach for medical applications. 70:1-70:4 - Patrizia Vizza, Mattia Cannistrà, Raffaele Giancotti, Pierangelo Veltri:
Image processing segmentation algorithms evaluation through implementation choices. 71:1-71:7 - Lorella Bottino, Marzia Settino, Mario Cannataro:
Scoliosis management through apps. 72:1-72:4 - Luca Barillaro, Giuseppe Agapito, Mario Cannataro:
Scalable deep learning for healthcare: methods and applications. 73:1-73:8 - Joan Peckham, Andy D. Perkins, Tayo Obafemi-Ajayi, Xiuzhen Huang:
NBT (no-boundary thinking): needed to attend to ethical implications of data and AI. 74:1-74:2 - Andy D. Perkins, Joan Peckham, Tayo Obafemi-Ajayi, Xiuzhen Huang:
Team building without boundaries. 75:1-75:3 - Asai Asaithambi, Chandrika Rao, Swapnoneel Roy:
Implementing algorithms for sorting by strip swaps. 76:1-76:9
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