• Shoba Ranganathan, Shoba Ranganathan, NSCC

NSCC Singapore was established in 2015 as a National Research Infrastructure and manages Singapore’s first national petascale facility with high-performance computing (HPC) resources. NSCC supports the HPC and Artificial Intelligence (AI) needs of the Singapore research community, accelerating innovative solutions, exemplified by select biological and biomedical case studies.

• Robyn Ball, Robyn Ball, The Jackson Laboratory
• Matthew Gerring, Matthew Gerring, The Jackson Laboratory
• Alexander Berger, Alexander Berger, The Jackson Laboratory
• Molly Bogue, Molly Bogue, The Jackson Laboratory
• Hongping Liang, Hongping Liang, The Jackson Laboratory
• David Walton, David Walton, The Jackson Laboratory
• Vivek Philip, Vivek Philip, The Jackson Laboratory
• Erich Baker, Erich Baker, Belmont University
• Elissa Chesler, Elissa Chesler, The Jackson Laboratory

Functional genomics has generated a wealth of gene regulatory information across species and research has shown that variants can be identified within each species that have similar effects on orthologous targets. We developed a knowledge graph across data resources and analytical services for cross-species analysis that includes GenomeMUSter (https://muster.jax.org), the Mouse Phenome Database (https://phenome.jax.org/), the meta-analysis server integrated with GenomeMUSter and the extensive collection of mouse phenotypic measurements in MPD, GeneWeaver (https://geneweaver.org), and VariantGraph db.

- GenomeMUSter is comprehensive and uniformly dense mouse variant resource comprised of imputed and measured allelic state data for 657 mouse strains at 106.8M sites
- The Mouse Phenome Database (MPD) is an NIH-recognized Biomedical Data Repository, curated and annotated with community standard ontologies, and integrated with a suite of analytical tools, including the meta-analysis server.
- GeneWeaver is a curated repository of genomic experimental results and ontology resources with an analytical tool suite that enables users to perform cross-species integrated functional genomics
- VariantGraph database is a Neo4j graph comprised of 32B relations among mouse and human variants, transcripts, genes, and regulatory peaks that enables evidenced-based identification of variants and genes with similar effects on orthologous targets

We will demo the knowledge graph and illustrate approaches to identify and characterize mouse-human effects with orthologous targets using motivating examples of cross-species multi-population multi-trait analytical approaches

• Erik Sonnhammer, Erik Sonnhammer, Stockholm University
• Davide Buzzao, Davide Buzzao, Stockholm University

The FunCoup database (https://FunCoup.org) provides comprehensive functional association networks of genes/proteins that were inferred by integrating massive amounts of multi-omics data, combined with orthology transfer. We will showcase how its unique online tools can be used to gain functional insights and answer scientific questions with network biology.

• Rami Mehio

Research and medical genomics require comprehensive and scalable solutions to drive
the discovery of novel disease targets, evolutionary drivers, and genetic markers with
clinical significance. This necessitates a framework to identify all types of variants
independent of their size (e.g., SNV/SV) or location (e.g., repeats). Here we present
DRAGEN that utilizes novel methods based on multigenomes mapping, hardware
acceleration, and machine learning based variant detection to provide novel insights
into individual genomes with ~30min computation time (from raw reads to variant
detection). DRAGEN outperforms all other state-of-the-art methods in speed and
accuracy across all variant types (SNV, indel, STR, SV, CNV) and further incorporates
specialized methods to obtain key insights in medically relevant genes (e.g., HLA, SMN,
GBA). We showcase DRAGEN across 3,202 genomes and demonstrate its scalability,
accuracy, and innovations to further advance the integration of comprehensive
genomics for research and medical applications.

• Etai Jacob

Modern clinical trials capture numerous clinicogenomic measurements. Manual discovery of predictive biomarkers is challenging. We introduce a framework which explores predictive biomarkers in a systematic and unbiased manner using contrastive learning. Applied to real data, our framework found biomarkers identifying IO-treated individuals who survive longer than those treated with chemotherapy.

• Venus Lau, Venus Lau, Magna Labs

Evaluation of bioinformatics pipeline performance (accuracy, robustness, and consistency) is critical both for developing and optimizing top-class algorithms, and for proving and maintaining the quality and reproducibility of these tools. Bioinformatics data is large, complex, and challenging to test, and many teams lack the time and resources to test effectively and efficiently, slowing development and introducing downstream risks and maintenance burdens.

Miqa is a biologist-friendly software quality assurance (QA) platform that can automate bioinformatic tool validation, benchmarking or troubleshooting as frequently as every code change. It allows you to build custom tests & benchmarking metrics for any data type, and is agnostic to programming language (Python, R, C++, etc.), workflow & containerization technologies (Nextflow, Snakemake, Docker) and cloud/execution platforms. We will demonstrate how to easily set-up automated software tests, customize QA metrics and generate interactive reports for comprehensive bioinformatic evaluation within minutes, on common data types like BAM, FASTQ, VCF, BED, and CSV/TSV/JSON, as well as custom pipeline outputs, and how it can be applied to a variety of technology types and disciplines.

• Aurélien Luciani, Aurélien Luciani, EMBL-EBI

The Universal Protein resource – UniProt – after its more than 20 years of existence, is now a
fundamental component in the bioinformatics and molecular biology community, providing a
comprehensive, high-quality, and freely accessible resource of protein sequence and functional
information. Recognizing the continuous evolution in data analysis needs and technology, and the
exponential growth of biological data, UniProt has undergone a significant update to enhance its
interface, functionalities, and overall user experience. This presentation aims to introduce these
transformative changes to the participants of the conference.
Our presentation will:
- Showcase the updated look and improved navigational functionalities of the new UniProt
website.
- Detail the advancements in the API that facilitate more efficient data retrieval and
integration.
- Highlight the enhanced data visualization tools that provide intuitive insights into protein
functions, interactions, and structures.
- Demonstrate the optimized processes for data export and sharing, which cater to both
academic and industrial research needs.
- Engage with both new and veteran UniProt users to gather feedback and discuss potential
future enhancements, helping us define a development roadmap that is based on user feedback

• Camilo Buscaron

Bioinformatics research continues to advance at an increasing scale with the help of techniques such as next-generation high-throughput sequencing algorithms, computational mass spectrometry, computational biophysics and the availability of tools to support automation of bioinformatics processes and workloads. With this growth, a large amount of biological data gets accumulated at an unprecedented rate, demanding high-performance and high-throughput computing technologies for processing such datasets. The use of hardware accelerators, and massively parallel heterogeneous compute systems accelerates the processing of big data in high-performance computing environments. Enabling higher degrees of parallelism to be achieved, thereby increasing computational throughput. In this talk, we will discuss the state of the art architectures enabling the acceleration and growth of computational biology workloads and algorithms.