Ecology, environment
and agriculture

Ecosystems bioinformatics in ecology and agriculture

Session chairs: Natasha Glover & Guillem Salazar

Session description: The living world presents numerous intricate complexities that we strive to understand by combining data analysis approaches with observation and experiments. Ecosystems vary greatly in size, diversity and functioning, for example from whole oceans, to the human gut microbiome, to simplified model systems that we use to understand interactions between organisms and their environment. Development of new bioinformatics tools and computational approaches enable us to infer complex evolutionary histories and adaptive changes, and relate these to changing ecosystems. These methods help us understand the dynamics and equilibria ruling the living world in a changing environment, and offer real applications from biotechnology to biomedical research, as well as in conservation biology, ecology, and agriculture. Sequencing data provide a large and varied source of information that require tools and models to investigate patterns of micro- and macro-evolutionary processes within and between species. This session aims to showcase the research of SIB groups working on unravelling the dynamics and mechanisms shaping the distribution and abundance of populations and underlying interactions, often with applications to ecology and agriculture.

Topics include but are not limited to: speciation biology; microbiomes of all shapes and sizes; eukaryotic and prokaryotic diversity; research applications in biotechnology, agriculture, or ecosystems management; quantitative models; morphology; host-microbe interactions; ecological and evolutionary factors in communities.

Evolution and phylogeny 

Evolutionary modelling with trees and beyond

Session chairs: Richard Neher & Ana Morales-Arce

Session description: Comparative genomic analyses within and across species can illuminate the forces driving evolutionary processes. Phylogenetics forms a cornerstone of such analyses, as it provides the evolutionary framework of the relationships between species or individuals upon which many inferences are based. In addition, most organisms exchange genetic information horizontally in one form or another. The development of models and software to better understand the evolution of organisms aims to take advantage of the growing amounts of genetic and genomic data that catalogue life on our planet. This often involves taking into account the interplay of population structure, trait architecture, and selection to disentangle causes and consequences. Also critical are robust methods to infer evolutionary history from sequence alignments and integrate those inferences with traits and spatio-temporal information. Such approaches have important applications in epidemiology, public health and medicine, as well as in ecology and evolution.

Topics include but are not limited to: bioinformatics sequence analysis tools and models; statistical tools in population genetics; likelihood, Bayesian, and other methods; phylogenetics and phylogenomics; biostatistics; comparative genomics.

Genes and genomes

Navigating the rapidly expanding space of Genes and Genomes

Session chairs: Evgenia Kriventseva & Damian Szklarczyk

Session description: Genomics continues to be the fastest growing field of molecular biology and the volume of sequencing data has reached a petabase-scale requiring and enabling novel analytical methodologies. While we can quantify the uncovered genomic variability, predicting phenotypic variability still remains challenging. The additional layers of molecular phenotypes, the various ‘-omics’ data, promise a solution of bridging the genotypes to phenotypes, yet it comes with new levels of complexity. In this session we invite talks from SIB members that tackle these problems.

Topics include but are not limited to: bioinformatics tools for analysing genes and genomes; gene network analysis; gene regulation genomics; comparative genomics; structural variant identification; gene function prediction and analysis; genomic interactions; analysis of genome-scale data; chromatin biology; epigenetics and transcriptional regulation; gene and genome evolution.

Medicine and health

Immunology, health and disease

Session chairs: Valérie Barbié & Giancarlo Croce

Session description: Differences between individuals determine the susceptibility to infections, the response to treatments, or the risk of developing various diseases. In addition, diseases etiology is influenced by a complex mix of components, like genetic factors, environmental factors, or the immune system. Efforts in understanding health and disease, and the role of the immune system, notably involve various genomics approaches, like genome-wide association studies, to identify variants associated with  specific traits. Transcriptomics and proteomics are also widely used, for example to identify differences in gene expression patterns between healthy and diseased populations. More recently, single-cell omics technologies have emerged, allowing to dissect the immune response at the single-cell level and characterize immune receptor repertoires. In this session we welcome contributions of data-driven efforts that aim at gaining a deeper understanding of health, disease and treatment, with a focus on immunology.

Topics include but are not limited to: immunology, genetic risks, risk factors, mutational burden, ‘omics technologies, machine learning, complex traits, precision medicine.

New methods in
bioinformatics

Mathematical and computational approaches to solve biological problems

Session chairs: Patrick Ruch & Sarah Brüningk    

Session description: The quantity of data generated by life sciences has grown exponentially over the years, but finding good ways to handle and analyse these massive data is still a major challenge. It is also necessary to explore them with a systematic approach to reveal the behaviour of the system as a whole rather than as the sum of its parts. Hence, this session of SIB days 2022 brings together researchers to discuss statistical and algorithmic approaches to improve data management, analysis, curation, and interpretation.

Topics include but are not limited to: text mining, machine learning, language models and pattern recognition; Bayesian approaches; read mapping for second and third generation sequencing technologies; analysis of high-throughput biological data (transcriptomics, proteomics, metabolomics, fluxomics); synthetic data generation; techniques for managing (e.g., data compression) and visualizing massive amount of sequencing data; methods for analysis of RNA sequencing (RNA-seq) data, including RNA expression, novel transcript assembly and splicing; methods for novel sequencing technologies such as single-cell sequencing, linked-read sequencing and Hi-C; epigenetics and gene regulation, including ChIP-seq analysis, methylation profiling, and histone modification; curation support tools; personalized health.

Proteins and proteomes 

Proteins and proteomes, from data to knowledge 

Session chairs: Bernd Wollscheid & Fanny Krebs

Session description: Proteins are key for nearly every task performed by a living organism, from shaping cells to defending them against pathogens. Recent technological advances allow protein characterisation at a larger scale, but there remains a crucial need for further integrating the data generated in order to improve our understanding of proteomes and to find novel biomarkers or drug targets. In this session, we are interested in everything relating to proteins, such as measuring and analysing their expression levels, their modifications, their interactions, and their biological roles.

Topics include but are not limited to: development of novel mass spectrometry tools and workflows for proteomics, immunoproteomics and metaproteomics; annotation and prediction of protein function; prediction and characterization of protein-protein interactions, as well as interactions with small molecules, DNA or RNA; analysis and annotation of proteoforms and post-translational modifications; discovery of biomarkers for health and disease; protein production and bioengineering; antibody-based studies.

Structural biology 

Structural bioinformatics: innovative tools to address bio-macromolecular structure and dynamics

Session chairs: Andrea Cavalli & Maria Marcaida Lopez

Session description: Three-dimensional structures of bio-macromolecules constitute an invaluable source of information to understand and predict the consequences of polymorphisms and somatic mutations, while they remain the cornerstone of structure-based drug design and protein engineering. Technical progress, particularly in cryo-electron microscopy, is providing an ever-increasing amount of high-quality experimental data, which requires computational approaches to process. These advances facilitate the study of protein flexibility and conformational variability. These data are also being integrated with information regarding biology and function, existing variants, and binding partners such as proteins or drug-like molecules. Moreover, deep learning has revolutionized the theoretical prediction of bio-macromolecule tertiary and quaternary structures, opening new avenues to study complex systems. This session is dedicated to projects related to the collection, prediction, dissemination and use of bio-macromolecular structures, as well as the study of their conformational variability.

Topics include but are not limited to: databases of bio-macromolecular structures; theoretical prediction and experimental characterization of tertiary and quaternary bio-macromolecular structures, including X-ray crystallography, NMR spectroscopy, electron microscopy and small angle X-ray scattering; molecular simulation and modelling; drug design; protein engineering; personalized medicine.

Systems biology  

Standards, analyses and trends in systems biology

Session chairs: Enkelejda Miho & Daniele Tavernari

Session description: Systems such as molecules, cells, tissues, and organisms at last, have a complex structure. At each of these levels, single entities interact and give rise to emergent collective behaviours. Data are investigated with various preprocessing pipelines and analysis methods in order to understand and characterize health and disease at the element and system level. Molecular omics at the bulk, single-cell and spatially-resolved levels are integrated with novel algorithmic approaches, and encoded as input for large-scale networks and machine learning frameworks e.g., support vector machines, random forests, neural networks. We discuss i) standards in current systems biology methods and the impact of custom pipelines, ii) novel analytic frameworks to uncover structure and interactions at the systems and entity level across health and disease, and iii) trends in real-world data integration for precision medicine. 

Open questions:

1. What are current standards in systems biology? What are the efforts in benchmarking methods? What is the impact of customized pipelines on results?

2. What are the current analytic frameworks for omics data integration, encoding and analysis? What are the challenges?

3. What are the current efforts and trends in real-world data combination with electronic health records (ELR), clinical parameters and laboratory tests?

Topics include but are not limited to: standards; machine learning; single-cell data; spatial transcriptomics and proteomics; cell-cell interactions; data integration; immune repertoires; B-cell receptor; T-cell receptor; precision oncology; autoimmune diseases; systems immunology;systems medicine; precision medicine; real-world data.