HPC-BOD 2024

5th International Workshop on High Performance Computing, Big Data Analytics and Integration for Multi-Omics Biomedical Data 

In conjunction with IEEE BigData 2024
Dec. 15-18, 2024 Washington DC USA

Important Dates:
Due date for full workshop papers submission: Oct 15, 2024
Notification of paper acceptance to authors: Nov 4, 2024
Camera-ready of accepted papers: Nov 20, 2024
Workshops: Dec 15-18, 2024

The submission link is: Submit Paper Here

Full papers (10 pages), short-papers (5 pages), and extended-abstracts (2 pages) are welcome. 

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HPC-BOD 2024 Call For Papers

Enormous amounts of data are being produced using modern technologies such as next generation sequencing machines, high-throughput mass spectrometers, and imaging instruments (such as MRI, fMRI, WSI etc.). The availability of such large and heterogeneous datasets creates challenges in terms of storage, transmission, computation, integration, and analysis. In order to process such data in a timely manner, big data analytics techniques and high-performance computing (HPC) is becoming an essential component in systems biology, bioinformatics and computational biology.

The goal of this workshop is to provide a forum for professionals and academics alike to discuss latest research in scalable machine-learning solutions to these compute-intensive and data-intensive problems related to systems biology. We are especially interested in HPC algorithms, big data analytic techniques, and machine learning/deep learning algorithms for integration of large-scale high-throughput multi-omics data sets.

The workshop will feature submitted papers as well as invited papers and talks from reputed researchers in the field of big data analytics, HPC and computational biology.

This will be 5th time that we will be arranging this workshop. The previous version of the workshop has appeared in PLOS One Special Collection.

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Thrust 1: Integration of Big Multi-Omics Data.

Areas of interest within computational life sciences include (but not limited to):

Computational genomics and metagenomics.
Genome assembly, long/short read data structures, read mapping, clustering, variant analysis, error correction, genome annotation, and other computational problems in large-scale genomics

Computational proteomics and proteogenomics.
Peptide identification from Big Mass Spectrometry data including database search and de novo methods, Genome annotations via mass spectrometry, Identification of post-translational modifications, Structural genomics via mass spectrometry, Protein-protein interactions and other computational problems in large-scale proteomics

Network biology methods for multi-omics integration.
Network representation learning (e.g., deep learning on graphs and network embedding), higher-order network analysis (network motifs/graphlets and networks of networks), inference of biological networks (e.g., gene regulatory networks, competing endogenous RNA networks, link prediction), comparison of biological networks (network alignment analysis and alignment-free network comparison), network-based personalized medicine (e.g., drug response prediction and drug target prediction)

Computational Neuroinformatics and Connectomics
Standardization in multiscale and multimodal modeling, Computational infrastructure for neuroscience: automation/pipelines, machine learning in neuroscience, reproducible neuroscience + open science

Other Omics and Integration for Systems Biology
Other computational problems in omics including but not limited to Epigenomics, Lipidomics, Glycomics, Foodomics, Transcriptomics, Metabolomics and methods to integrate these omics datasets to get systems biology insights of disease pathophysiology.

Thrust 2: High-Performance Computing for Big Data Omics.

Areas of interest within HPC include (but are not limited to):

Parallel and distributed algorithms for big data Omics.
Scalable machine learning, parallel graph/sequence analytics, combinatorial pattern matching, optimization, parallel data structures, compression/decompression, multicore, manycore, CPU/GPU, FPGA, system-on-chip, hardware accelerators, energy-aware architectures, hardware/software co-design

Accessible Scientific workflows for Big Data Omics.
Data management, Data wrangling, Automated workflows, Cloud-enabled solutions for computational biology, and Energy-aware High-Performance Biological Applications

Big Data Omics Analytics, Infrastructure, and Management.
Novel techniques to deal with big omics data including but not limited to sketching, sampling, streaming, compression/decompression, succinct data-structures and algorithms, novel encoding techniques, efficient methods to integrate multi-omics data and Multimedia and Multi-structured Omics data

Hardware Acceleration for Big Omics Data.
FPGA/CGRA/GPU accelerators for Big Data applications, domain-specific and heterogeneous architectures, and design that can accelerate machine-learning aspects of dealing with big omics data.

Submission guidelines

Please submit a full-length paper (up to 10 page IEEE 2-column format, reference pages counted in the 10 pages, short paper (up to 5 pages IEEE 2-column format, including references) or extended abstract (2 pages IEEE 2-column format, including references) through the online submission system. Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines. See link for more info: https://www.ieee.org/conferences/publishing/templates.html

HPC-BOD technical program committee will review all submissions on the basis of their originality, technical soundness, significance, presentation, and relevance to the conference attendees.

All submissions will be peer-reviewed by members from the program committee using a single-blind review process. At the time of submission, the author list should be final. Any subsequent changes to the author list post-submission needs to be done with the approval of the program chairs. Acceptance of any of these would mean an oral presentation. However, the authors would have to pay registration for the paper to be included in the IEEE BigData proceedings.

The submission link is: Submit Paper Here

Important Dates:

Due date for full workshop papers submission: Oct 15, 2024
Notification of paper acceptance to authors: Nov 4, 2024
Camera-ready of accepted papers: Nov 20, 2024
Workshops: Dec 15-18, 2024

Selected papers will possibly be published in Plos Special Collections (web-link) and in the Journal of Computational Biology and Bioinformatics (JBCB) (web-link). 

Workshop Organization

Workshop Chairs:
Fahad Saeed (Florida International University, Miami FL USA)
Serdar Bozdag (University of North Texas, Denton, Texas USA)

Steering and advisory committee:
Alexey Nesvizhskii (University of Michigan, Ann Arbor)
Dan Jacobson (Oak Ridge National Laboratory)

Program Committee
TBA

Keynote Speaker(s)
TBA

Previous Workshops

HPC-BOD 2020

HPC-BOD 2021

HPC-BOD 2022

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