default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID11th BCB 2020: Virtual Event, USA
- BCB '20: 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Virtual Event, USA, September 21-24, 2020. ACM 2020, ISBN 978-1-4503-7964-9
Sequences & Networks I
- Tobias Rubel, Anna M. Ritz:
Augmenting Signaling Pathway Reconstructions. 1:1-1:10 - Chaitanya Aluru, Mona Singh:
Identifying Evolutionary Origins of Repeat Domains in Protein Families. 2:1-2:11 - Ali Jazayeri, Sara Pajouhanfar, Sadaf Saba, Christopher C. Yang:
Modularity Analysis of Bipartite Networks and Multivariate ANOVA for Identification of Differentially Expressed Proteins in a Mouse Model of Down Syndrome. 3:1-3:8 - Vipin Vijayan, Shawn Gu, Eric T. Krebs, Lei Meng, Tijana Milenkovic:
Pairwise Versus Multiple Global Network Alignment. 4:1 - Ananthan Nambiar, Maeve Heflin, Simon Liu
, Sergei Maslov, Mark Hopkins, Anna M. Ritz:
Transforming the Language of Life: Transformer Neural Networks for Protein Prediction Tasks. 5:1-5:8
Cancer Omics I
- Felipe O. Giuste, Mythreye Venkatesan, Conan Zhao, Li Tong, Yuanda Zhu, Shriprasad R. Deshpande, May D. Wang:
Automated Classification of Acute Rejection from Endomyocardial Biopsies. 6:1-6:9 - Banabithi Bose, Serdar Bozdag:
CTDPathSim: Cell line-tumor deconvoluted pathway-based similarity in the context of precision medicine in cancer. 7:1-7:10 - Fatima Zare, Javad Noorbakhsh, Tianyu Wang, Jeffrey H. Chuang, Sheida Nabavi:
Integrative Deep Learning for PanCancer Molecular Subtype Classification Using Histopathological Images and RNAseq Data. 8:1-8:8 - Gulden Olgun, Öznur Tastan:
Functional Enrichment Analysis of Deregulated Long Non-Coding RNAs in Cancer Based on their Genomic Neighbors. 9:1-9:10 - Zhong Chen, Andrea Edwards, Kun Zhang:
Fusion Lasso and Its Applications to Cancer Subtype and Stage Prediction. 10:1-10:8
Regulatory Genomics
- Aditya Pratapa, Amogh P. Jalihal, Jeffrey N. Law, Aditya Bharadwaj, T. M. Murali:
How to build regulatory networks from single-cell gene expression data. 11:1 - Katie L. Ovens, B. Frank Eames, Ian McQuillan:
The impact of sample size and tissue type on the reproducibility of gene co-expression networks. 12:1-12:10 - Mercè Llabrés, Francesc Rosselló, Gabriel Valiente:
A Generalized Robinson-Foulds Distance for Clonal Trees, Mutation Trees, and Phylogenetic Trees and Networks. 13:1-13:10 - Ruby Sharma, Xuye Luo, Sajal Kumar, Mingzhou Song:
Three Co-expression Pattern Types across Microbial Transcriptional Networks of Plankton in Two Oceanic Waters. 14:1-14:10 - Ye Wu, Ruibang Luo, Tak Wah Lam, Hing-Fung Ting, Junwen Wang:
Translocator: local realignment and global remapping enabling accurate translocation detection using single-molecule sequencing long reads. 15:1-15:7
Sequences & Networks II
- Abhijit Mondal, Misagh Kordi, Mukul S. Bansal:
A Supervised Machine Learning Approach for Distinguishing Between Additive and Replacing Horizontal Gene Transfers. 16:1-16:11 - Lorraine A. K. Ayad, Panagiotis Charalampopoulos, Solon P. Pissis:
SMART: SuperMaximal approximate repeats tool. 17:1 - Mehmet Eren Ahsen, Yoojin Chun, Alexander Grishin, Galina Grishina, Gustavo Stolovitzky, Gaurav Pandey, Supinda Bunyavanich:
NeTFactor, a framework for identifying transcriptional regulators of gene expression-based biomarkers. 18:1-18:13 - Subrata Saha, Zigeng Wang, Sanguthevar Rajasekaran:
HMSC: a Hybrid Metagenomic Sequence Classification Algorithm. 19:1-19:6 - Jan Zrimec:
Structural representations of DNA regulatory substrates can enhance sequence-based algorithms by associating functional sequence variants. 20:1-20:6 - William Gasper, Kathryn M. Cooper, Nathan Cornelius, Hesham Ali, Sanjukta Bhowmick:
Characterization of S. cerevisiae Protein Complexes by Representative DDI Graph Planarity. 21:1-21:6
Cancer Omics II
- Bino A. Varghese, Frank Chen, Darryl Hwang, Suzanne L. Palmer, Andre Luis De Castro Abreu, Osamu Ukimura, Monish Aron, Manju Aron, Inderbir S. Gill, Vinay A. Duddalwar, Gaurav Pandey:
Objective risk stratification of prostate cancer using machine learning and radiomics applied to multiparametric magnetic resonance images. 22:1-22:10 - Yixing Jiang, Kristen Alford, Frank Ketchum, Li Tong, May D. Wang:
TLSurv: Integrating Multi-Omics Data by Multi-Stage Transfer Learning for Cancer Survival Prediction. 23:1-23:10 - Saloni Agarwal, Mohamedelfatih Eltigani Osman Abaker, Xinyi Zhang, Ovidiu Daescu, Donald A. Barkauskas, Erin R. Rudzinski, Patrick Leavey:
Rhabdomyosarcoma Histology Classification using Ensemble of Deep Learning Networks. 24:1-24:10 - Sudhir Ghandikota, Anil G. Jegga:
A multi-context feature learning approach to identify disease-specific gene neighborhoods. 25:1-25:6 - Junjie Chen, Mohammad Erfan Mowlaei, Xinghua Shi:
Population-scale Genomic Data Augmentation Based on Conditional Generative Adversarial Networks. 26:1-26:6
Structural Bioinformatics
- Fardina Fathmiul Alam, Amarda Shehu:
Variational Autoencoders for Protein Structure Prediction. 27:1-27:10 - Akanksha Pandey, Edward L. Braun:
Protein evolution is structure dependent and non-homogeneous across the tree of life. 28:1-28:11 - Spencer Krieger, John D. Kececioglu:
Predicting protein secondary structure by an ensemble through feature-based accuracy estimation. 29:1-29:10 - Spencer Krieger, John D. Kececioglu:
Boosting the accuracy of protein secondary structure prediction through nearest neighbor search and method hybridization. 30:1 - Xiao Chen, Nasrin Akhter, Zhiye Guo, Tianqi Wu, Jie Hou, Amarda Shehu, Jianlin Cheng:
Deep Ranking in Template-free Protein Structure Prediction. 31:1-31:10
COVID-19 I
- Niharika Pandala, Casey A. Cole, Devaun McFarland, Anita Nag, Homayoun Valafar:
A Preliminary Investigation in the Molecular Basis of Host Shutoff Mechanism in SARS-CoV. 32:1-32:9 - David Oniani, Yanshan Wang:
A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19. 33:1-33:9 - Yue Li, Pratheeksha Nair, Zhi Wen, Imane Chafi, Anya Okhmatovskaia, Guido Powell, Yannan Shen, David L. Buckeridge:
Global Surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model. 34:1-34:14 - Tim Kosfeld, Jonathan McMillan, Richard J. DiPaolo, Jie Hou, Tae-Hyuk Ahn:
Performance Evaluation of Viral Infection Diagnosis using T-Cell Receptor Sequence and Artificial Intelligence. 35:1-35:10 - Wenqi Shi, Li Tong, Yuchen Zhuang, Yuanda Zhu, May D. Wang:
EXAM: An Explainable Attention-based Model for COVID-19 Automatic Diagnosis. 36:1-36:6
HTS Data I
- Jacob M. Schreiber, Timothy J. Durham, William S. Noble, Jeffrey A. Bilmes:
Avocado: Deep tensor factorization characterizes the human epigenome via imputation of tens of thousands of functional experiments. 37:1 - Luis Rueda, Nazia Fatima:
iSOM-GSN: An Integrative Approach for Transforming Multi-omic Data into Gene Similarity Networks via Self-organizing Maps. 38:1 - Jacob M. Schreiber, Deepthi Hegde, William S. Noble:
Zero-shot imputations across species are enabled through joint modeling of human and mouse epigenomics. 39:1-39:9 - Ritambhara Singh, Pinar Demetci, Giancarlo Bonora, Vijay Ramani, Choli Lee, He Fang, Zhi-jun Duan, Xinxian Deng, Jay Shendure, Christine Disteche, William Stafford Noble:
Unsupervised manifold alignment for single-cell multi-omics data. 40:1-40:10 - Luqin Gan, Giuseppe Vinci, Genevera I. Allen:
Correlation Imputation in Single cell RNA-seq using Auxiliary Information and Ensemble Learning. 41:1-41:6
COVID-19 II
- Junheng Hao, Chelsea J.-T. Ju, Muhao Chen, Yizhou Sun, Carlo Zaniolo, Wei Wang:
Bio-JOIE: Joint Representation Learning of Biological Knowledge Bases. 42:1-42:10 - Scott LeGrand, Aaron Scheinberg, Andreas F. Tillack, Mathialakan Thavappiragasam, Josh Vincent Vermaas, Rupesh Agarwal, Jeff Larkin, Duncan Poole, Diogo Santos-Martins, Leonardo Solis-Vasquez, Andreas Koch, Stefano Forli, Oscar R. Hernandez, Jeremy C. Smith, Ada Sedova:
GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research. 43:1-43:10 - Hao-Ren Yao, Der-Chen Chang, Ophir Frieder, Wendy Huang, I-Chia Liang, Chi-Feng Hung:
Cross-Global Attention Graph Kernel Network Prediction of Drug Prescription. 44:1-44:10 - Allison M. Rossetto, Wenjin Zhou:
GANDALF: Peptide Generation for Drug Design using Sequential and Structural Generative Adversarial Networks. 45:1-45:10 - Roger A. Hallman, Anjali Chikkula, Temiloluwa Prioleau:
Predicting Criticality in COVID-19 Patients. 46:1-46:7
Mining & Scalable Tools
- Ellie Small, Javier Cabrera, John B. Kostis:
Abstract Mining. 47:1-47:6 - Fatemeh Rouzbeh, Ananth Grama, Paul M. Griffin, Mohammad Adibuzzaman:
Collaborative Cloud Computing Framework for Health Data with Open Source Technologies. 48:1-48:10 - William Gasper, Parvathi Chundi, Dario Ghersi:
MeSH Indexing Using the Biomedical Citation Network. 49:1-49:8 - Cui Su, Jun Pang:
A Dynamics-based Approach for the Target Control of Boolean Networks. 50:1-50:8
Genomics
- Tyler C. Shimko, Polly M. Fordyce, Yaron Orenstein:
DeCoDe: degenerate codon design for complete protein-coding DNA libraries. 51:1 - Morgan Carothers, Joseph Gardi, Gianluca Gross, Tatsuki Kuze, Nuo Liu, Fiona Plunkett, Julia Qian, Yi-Chieh Wu:
An Integer Linear Programming Solution for the Most Parsimonious Reconciliation Problem under the Duplication-Loss-Coalescence Model. 52:1-52:12 - Pavel Avdeyev, Max A. Alekseyev:
Linearization of Ancestral Genomes with Duplicated Genes. 53:1-53:10 - Chaochao Yan, Sheng Wang, Jinyu Yang, Tingyang Xu, Junzhou Huang:
Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation. 54:1-54:7
Medical Informatics I
- Lucas Jing Liu, Hongwei Zhang, Jianzhong Di, Jin Chen:
ELMV: an Ensemble-Learning Approach for Analyzing Electrical Health Records with Significant Missing Values. 55:1-55:10 - Yuhui Du, Bang Li, Yuliang Hou, Vince D. Calhoun:
A deep learning fusion model for brain disorder classification: Application to distinguishing schizophrenia and autism spectrum disorder. 56:1-56:7 - Jiandong Wang, Sajal Kumar, Mingzhou Song:
Joint Grid Discretization for Biological Pattern Discovery. 57:1-57:10 - Elham Rastegari, Donovan Orn, Hesham H. Ali:
Smart Computational Approaches with Advanced Feature Selection Algorithms for Optimizing the Classification of Mobility Data in Health Informatics. 58:1-58:9 - Luca Tomasetti, Kjersti Engan, Mahdieh Khanmohammadi, Kathinka Dæhli Kurz:
CNN Based Segmentation of Infarcted Regions in Acute Cerebral Stroke Patients From Computed Tomography Perfusion Imaging. 59:1-59:8
HTS Data II
- Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch:
Staging Epileptogenesis with Deep Neural Networks. 60:1-60:10 - Wei Yang, Jeffrey A. Bilmes, William Stafford Noble:
Submodular sketches of single-cell RNA-seq measurements. 61:1-61:6 - Shibiao Wan, Junil Kim, Yiping Fan, Kyoung-Jae Won:
Processing Millions of Single Cells by SHARP. 62:1 - Keith Mitchell, Jaqueline J. Brito, Igor Mandric, Qiaozhen Wu, Sergey Knyazev, Sei Chang, Lana S. Martin, Aaron Karlsberg, Ekaterina Gerasimov, Russell Littman, Brian L. Hill, Nicholas C. Wu, Harry (Taegyun) Yang, Kevin Hsieh, Linus Chen, Eli Littman, Taylor Shabani, German Enik, Douglas Yao, Ren Sun, Jan Schroeder, Eleazar Eskin, Alex Zelikovsky, Pavel Skums, Mihai Pop, Serghei Mangul:
Benchmarking of computational error-correction methods for next-generation sequencing data. 63:1 - Sairam Behera, Jitender S. Deogun, Etsuko N. Moriyama:
MinIsoClust: Isoform clustering using minhash and locality sensitive hashing. 64:1-64:7
Medical Informatics II
- Riyad Hakim, Saeed Salem:
Efficiently mining rich subgraphs from vertex-attributed graphs. 65:1-65:9 - Aly A. Valliani, John T. Schwartz, Varun Arvind, Amir Taree, Jun S. Kim, Samuel K. Cho:
Multi-Site Assessment of Pediatric Bone Age Using Deep Learning. 66:1-66:5 - Alexander F. B. Carmichael, Deepayan Bhowmik, Johanna L. Baily, Andrew Brownlow, George J. Gunn, Aaron Reeves:
Ir-Man: An Information Retrieval Framework for Marine Animal Necropsy Analysis. 67:1-67:9 - William Das, Shubh Khanna:
A Novel Pupillometric-Based Application for the Automated Detection of ADHD Using Machine Learning. 68:1-68:6
POSTER SESSION: BCB Posters
- Ronald J. Nowling, Rafael Reple Geromel, Benjamin Halligan:
Filtering STARR-Seq Peaks for Enhancers with Sequence Models. 69:1 - Ronald J. Nowling, Christopher R. Beal, Scott J. Emrich, Susanta K. Behura, Marc S. Halfon, Molly Duman-Scheel:
PeakMatcher: Matching Peaks Across Genome Assemblies. 70:1 - Anna Antoniadi, Miriam Galvin, Mark Heverin, Orla Hardiman, Catherine Mooney:
Using Patient Information for the Prediction of Caregiver Burden in Amyotrophic Lateral Sclerosis. 71:1 - Mengmeng Kuang, Hing-Fung Ting:
A data-centric pipeline using convolutional neural network to select better multiple sequence alignment method. 72:1 - Fatemeh Rouzbeh, Ananth Grama, Paul M. Griffin, Mohammad Adibuzzaman:
A Unified Cloud-Native Architecture For Heterogeneous Data Aggregation And Computation. 73:1 - Yuan Zhuang, Kara L. Cerveny, Anna M. Ritz:
Prefix/Suffix Variation in Retinoic Acid Response Elements. 74:1 - Heyuan Zeng, Anna M. Ritz:
Graphery: a Biological Network Algorithm Tutorial Webservice. 75:1 - Dondra Bailey, Kawther Abdilleh, Boris Aguilar, Alexis McClary:
Multi-omics characterization of Microtubule-actin cross linking factor 1 (MACF1) using the ISB-Cancer Genomics Cloud. 76:1 - Yassin Mreyoud, Tae-Hyuk Ahn:
Deep Neural Network Modeling for Phenotypic Prediction of Metagenomic Samples. 77:1 - Ayoub Bagheri, T. Katrien J. Groenhof, Wouter B. Veldhuis, Pim A. de Jong, Folkert W. Asselbergs, Daniel L. Oberski:
Multimodal Learning for Cardiovascular Risk Prediction using EHR Data. 78:1 - Sagnik Banerjee, Margaret Woodhouse, Roger P. Wise, Priyanka Bhandary, Taner Z. Sen, Carson M. Andorf:
FINDER: A fully automated pipeline to FIND accurate gene structures from proteins and RNA-Seq expression data. 79:1-79:2 - Rajitha Yasas Wijesekara, Ashwin Lahorkar, Kunal Rathore, Jayaraman K. Valadi:
RA2Vec: Distributed Representation of Protein Sequences with Reduced Alphabet Embeddings: RA2Vec: Distributed Representation. 80:1 - Yuhan Du, John Mehegan, Fionnuala M. McAuliffe, Catherine Mooney:
Prediction of Large for Gestational Age Infants in Overweight and Obese Women at Approximately 20 Gestational Weeks. 81:1 - Iván Carrera, Inês Dutra, Eduardo Tejera:
Representing Cellular Lines with SVM and Text Processing. 82:1 - Wayne Zachary, Hita Gupta:
Comparing Type 2 Diabetes Self-Management Apps Against the Needs of Low-Income Minority Patients: Is There An Implicit Functionality Bias? 83:1 - Gabriel A. Preising, Joshua J. Faber-Hammond, Suzy C. P. Renn, Anna M. Ritz:
A Protein-Protein Interactome for an African Cichlid. 84:1 - Kawther Abdilleh, Boris Aguilar, J. Ross Thomson:
Multi-omics data integration in the Cloud: Analysis of Statistically Significant Associations Between Clinical and Molecular Features in Breast Cancer. 85:1 - Allison M. Rossetto, Wenjin Zhou:
Novel Generated Peptides for COVID-19 Targets. 86:1 - Bhumika Arora:
Refinement of G protein-coupled receptor structure models: Improving the prediction of loop conformations and the virtual ligand screening performances. 87:1 - Jan Zrimec, Aleksej Zelezniak:
Learning the regulatory grammar of DNA for gene expression engineering. 88:1 - Salvador Eugenio C. Caoili:
Beyond B-Cell Epitopes: Curating Positive Data on Antipeptide Paratope Binding to Support Development of Computational Tools for Vaccine Design and Other Translational Applications. 89:1
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-02-27 22:32 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
