Talks and seminars featuring experts from around the world, open to everyone.
How robust benchmarking and large-scale data reuse are changing computational biology, and why reproducibility, data sharing and software usability decide whether a bioinformatics tool can be trusted.
How algorithms, software tools and metabolic models reveal the interactions inside microbial communities, and the feedback between environmental change, community structure and ecosystem impact.
An exploration of simulation and machine learning methods for predicting protein-ligand, protein-protein, and protein-membrane interactions.
All-atom enhanced-sampling simulations of three-quartet RNA G-quadruplex folding, which turns out to be a multi-pathway process with no simple structured intermediates, and a candid account of where current force fields fall short.
Hybrid ligand discovery methods that combine machine learning with physics-based simulation, applied to SARS-CoV-2 non-structural protein 3, amyloid beta-42 aggregation and antibiotic resistance proteins.
A GPU-accelerated pipeline running 4,752 alchemical free energy perturbation simulations to quantify how single mutations in dihydrofolate reductase change trimethoprim binding: antibiotic resistance predicted before it appears in the clinic.
A structure-based framework that joins genetic and structural data to explain what variants do: in cancer predisposition, in drug resistance, and in the tools her group builds to classify and predict variant effects.
A practical tour of the glycoinformatics resources behind GlyCosmos: the GlyTouCan glycan repository, integration with other omics fields, and the GlySpace Alliance's push for FAIR data sharing.
A residue interaction network model that describes a protein's native structure as a weighted graph and uses network centrality to propose putative allosteric sites for drug binding, demonstrated on GPCRs and other complexes.
PRESCOTT and ESCOTT for predicting the effect of amino-acid substitutions and deletions, together with a precomputed ESCOTT database covering 19,295 human proteins.
A follow-up to the earlier Linux terminal webinar, going past the basics into using the shell for data analysis and for automating the repetitive parts of a bioinformatics workflow.
Student-led research presentations and discussions
Dr. Elisa Frezza walks through computational strategies for modeling RNA structures and protein-RNA interactions, covering molecular dynamics simulations, normal mode analysis, and coarse-grained methods.
Computational and theoretical approaches to the conformational dynamics of enzymes and the evolutionary emergence of new enzymatic functions.
A webinar on the practical use of the ENCORE implementation, and on methods for improving reproducibility and transparency in computational research.
Network-based methods for extracting active network signatures from omics datasets and studying condition-specific signalling networks, and context-specific analysis of gene essentiality with CEN-tools.
A talk highlighting recent developments around the HADDOCK software: the role of integrative modelling in predicting the structure of biomolecular complexes, and modelling antibody–antigen interactions from sequence alone.
Using microfluidic live-cell imaging and the Prox-seq technology to understand how the NF-κB immune pathway processes complex signals, and how single-cell dynamics shape gene expression.
Machine learning and deep learning approaches for integrating heterogeneous biomedical data, predicting the functional properties of proteins, and discovering and designing new drug candidates.
The molecular mechanism behind TcdB's selective interaction with human Rho GTPases (Cdc42 and Rac1), through structural, dynamic and transcriptomic approaches.
A webinar on the importance of the Linux terminal for managing and analysing large, complex and varied biological datasets effectively.
Five students from Koç University present their research: drug-like molecules on protein-protein interaction interfaces, network models of cancer and neurodevelopmental disorders, tumour progression, vascular cognitive impairment, and drug response prediction.
Dr. Bayraktar presents cell2location, a Bayesian model for resolving fine-grained cell types in spatial transcriptomic data, and GBM-space, a multi-modal genomics approach to mapping tumour tissue architecture in glioblastoma.
Using interactome data and common genetic variation across more than 1000 traits to build a disease pleiotropy map, and to find the protein communities that may be therapeutic target hotspots.
An overview of how bioinformatics tools provide the basis for constructing mathematical models of diseases to understand disease mechanisms and design rational drugs on a whole-systems basis.
A comparative evaluation of 23 protein representation methods, examining the strengths of deep-learning-based approaches for predicting the functional properties of proteins.
New methods for efficiently measuring and predicting protein-RNA interactions: DeCoDe (efficient design of high-throughput experiments) and DeepUTR (prediction of mRNA decay dynamics).
Four students of Acıbadem University present their research: BRCA1 SNP co-occurrence, variant pathogenicity prediction, and mutated genes in leptomeningeal metastasis from breast and lung cancer.
Using ONT long-read technology and the 'Nexons' workflow to uncover how poison exons of splicing factors are regulated in human germinal centre B cells.
Deep learning based dense prediction networks for segmentation tasks in medical image analysis, with network architectures and loss functions designed for histopathological and in vivo imaging.
An expectation maximisation algorithm (BEEM-Static) for inferring ecological interaction networks from cross-sectional microbiome datasets, revealing enterotype structure and ecological dynamics.
Four graduate students from Gebze Technical University present their research in cancer dormancy, Parkinson's disease metabolism, Alzheimer's disease, and Klebsiella pneumoniae drug targets.
A framework that exploits the training dynamics of deep learning models to detect misannotated lncRNAs, reaching >91% AUC without the need for ribo-seq experiments.
A comparison of six web-based scoring tools in assessing the effect of kinase mutations on their interactions with inhibitors, using the new BINDKIN benchmark.
Barış Ekim introduces minimizer-space sequencing data analysis (mdBG), achieving orders-of-magnitude improvements in genome assembly speed and memory usage over existing methods.
Presentation of SPaRTAN, a computational method to link cell-surface receptors to transcription factors using CITE-seq datasets, applied to predict signaling-coupled TF states in tumor infiltrating CD8+ T cells.
Ancient DNA analysis of 40 individuals spanning 17,000–550 years from Yakutia and Lake Baikal, revealing gene flow events, Palaeo-Inuit ancestors, and Yersinia pestis in ancient Northeast Asia.
A study using Constraint Molecular Dynamics simulation to clarify how glycolytic enzymes are allosterically inhibited in a species-specific manner, enabling targeted drug design.
An in silico, in vitro, and in vivo investigation of cholinergic signals in cancer progression, including the role of CHRNA5 in breast cancer and zebrafish xenograft models for liver cancer.
Translational control in cancer and stromal cells, followed by a hands-on tutorial on transcriptome-wide analysis of translational efficiency.
An exploration of viral diversity dynamics at the protein sequence level, focusing on how viruses evade host immune responses through rapid mutation and the implications for vaccine design.
Presentation of CEN-tools, a website and Python package for interrogating gene essentiality from large-scale CRISPR screens across biological contexts including tissue of origin, mutation profiles, and drug response levels.
A convolutional neural network approach using Modified Inception and MobileNet models to detect and classify skin cancer types, evaluated on the HAM10000 dataset.
A comparative phylogenomic study of sex-related genes in Hexamita inflata, showing evidence for nuclear fusion and meiotic inter-homolog recombination in this diplomonad.
Investigation of how protein structure influences sequence evolution, focusing on the distribution of adaptive mutations along 3D protein structures and coevolution between positions.
Presentation of a new Python pipeline (ASHURE) for density-based clustering and error correction of metabarcodes using Oxford Nanopore sequencing, achieving >99% sequence accuracy for freshwater mock communities.
A Bayesian negative binomial multilevel model with mixed effects for projecting COVID-19 confirmed daily and cumulative cases in Türkiye, showing a decreasing epidemic curve under compliance with containment measures.
A summary of modern studies and approaches related to the Lewontin Paradox (the contradiction between population size and neutral genetic variation) with emphasis on the Hill-Robertson effect and linked selection.
A theoretical and empirical study of how multi-locus associative overdominance can amplify genetic diversity in low-recombination regions, with evidence of this phenomenon in the human genome.
A comparative study of SARS-CoV-2 genome variants identified by the Galaxy Project and INSaFLU workflows, presented by RSG-Türkiye active members.
A comprehensive phylogenetic analysis of SARS-CoV-2 genomes in Türkiye using 15,277 global sequences, revealing early introduction of the virus and multiple independent international transmission events.
An introduction to accessing The Cancer Genome Atlas repository and tools for multi-omics assessment of tumours, focusing on renal cell carcinomas.
An exploration of codon reassignments and unprecedented variants of the mitochondrial genetic code in the green algal order Sphaeropleales.
A historical and physical perspective on how molecular simulations can be thought of as in silico experiments, exploring the analogy between simulation and wet-lab experiments in structural biology.
MERLoT, a tool for reconstructing cellular lineage trees with many cell fates from single-cell transcriptomics, and for imputing temporal gene expression profiles along them.
An overview of applications of Artificial Neural Networks to Single Cell Genomics, Microscopy Imaging, and Genomics/Ancient DNA research, addressing the challenges of big data in life sciences.
How thousands of ancient and modern genomes, and new computational approaches, rewrote human evolutionary history: gene flow among hominins, structural variants, and pinpointing recent ancestry.
Turning a decade of microbiome sequencing data into predictive models for diagnosis, prognosis and therapy, and the methods needed to keep the results reproducible.
Using accurate evolutionary histories and manually curated alignments of NPC1 and GPRC6A to improve predictions of disease-causing amino acid substitutions in membrane receptors.
Good, better and best workflows for reproducibility: from data storage and cleaning through analysis to communicating the final result.
A zero-shot learning approach that transfers knowledge from well-characterised kinases to understudied ones, predicting phosphorylation sites for kinases with no prior data.
Web-based interactive platforms for single-cell RNA-seq, compared on usability, interface, developer support, performance at different file sizes, and the file formats they expect.
Presentation of Hercules, the first machine learning algorithm for long-read error correction using Hidden Markov Models, achieving higher mapping rates than existing methods.
Homology modelling and coarse-grained molecular dynamics for ligand-gated ion channels, and why alignment inaccuracy limits comparative models in the low sequence-similarity range.
Over 360 arthropod genomes and 1000 transcriptomes, and the bioinformatic resources that hold them: VectorBase, AphidBase, Ensembl Metazoa, NCBI-GenBank, OrthoDB and others.
How culture-independent sequencing turned microbiology into a data science, and what computational approaches revealed about humans as a collection of trillions of microbes.
An overview of how genomics, transcriptomics, and epigenetics are changing our understanding of molecular health, and the future challenges of high-throughput data analysis.
Reading human history out of genomes: the origins of our species in Africa, the Anglo-Saxon migration period seen through ancient DNA, and the peopling of North America.
Integrated genetic and epigenetic analysis of non-NF2 meningiomas, and CaSpER: an algorithm that identifies, visualises and integrates CNV events at multiscale resolution from single-cell and bulk RNA-Seq.
The validated FoundationOne® diagnostic assay for solid tumours: what it detects across 315 cancer-related genes, how it performs in clinical practice, and the first results from University Hospital Zurich.
Two deep learning methods for large-scale biological data: DEEPred, for predicting the functions of uncharacterised proteins, and DEEPscreen, for identifying novel drug candidates. Also where deep learning falls short.
A webinar on Microsatellite Instability in tumours: the impact of short tandem repeats on gene expression, epigenetics, and how these effects can be utilized for immunotherapy.
A webinar covering systems-wide analysis of brain cell metabolism, mapping transcriptome data for neurodegenerative diseases using reporter pathways, and constraint-based modelling of brain metabolic networks.
A webinar on how computational approaches and evolutionary genomics can help study conservation and biodiversity, including testing evolutionary models and understanding the evolutionary basis of adaptation.
An introduction to structural biology techniques and how to incorporate structural data into biomolecular simulations, especially docking, with discussion of integrative modeling published in Nature Methods.
Turning information design into practical guidelines for scientific figures: how a well-designed graphic can be concise and articulate, and how design focuses a viewer's attention.
The sixth webinar of the BioInfoNet series, on allosteric calcium sensors and their role in synaptic plasticity.
The fifth webinar of the BioInfoNet series, on molecular insights into the evolution of the testis in primates.
The fourth webinar of the BioInfoNet series, on discovering and genotyping structural variations from next-generation sequencing data.
The third webinar of the BioInfoNet series, on network modelling approaches for identifying personalized therapeutic strategies in glioblastoma.
A talk on computational metagenomics on the species level, part of the early BioInfoNet webinar series, exploring the challenges and opportunities of metagenomic data analysis.
The first webinar of the BioInfoNet series, presenting methods for reconstructing signaling network topology from steady state and dynamic perturbation data.
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