Decima Edizione della Giornata Toscana di Bioinformatica e Systems Biology,
7-8 settembre 2023
Auditorium di TLS - Fondazione Toscana Life Sciences. Ingresso: strada del Petriccio e Belriguardo, 35, Siena
|Opening and welcome remarks
A chat on the use and abuse of chatGTP in bioinformatics.Dr Marco Pellegrini, IIT-CNR
We will discuss the use (abuse), advantages, and limitations of chatGTP for several tasks in bioinformatics research. We will discuss issues related to writing, debugging and summarizing software using chatGTP as an AI assistant.
|Presentazione del Master in Bioinformatica e Data ScienceProf Moreno Falaschi, Univ. di Siena
Biological sequence alignment and algorithms based on dynamic programming.Prof. Sara Brunetti, Univ. di Siena
The problem of aligning two or more biological sequences is of main importance for several problems in comparative genomics. Sequence alignment permits to highlight regions of high similarity and regions where the sequences differ, as a consequence of structural and evolutionary relationships between organisms.
In this tutorial we present computational approaches to pairwise sequence alignment with analysis of the complexity of these algorithms. The algorithms use the dynamic programming technique. This same idea permits to solve three main subproblems, we refer as global, semiglobal and local alignment problems respectively when both sequences are entirely compared, one is entirely aligned with a fragment of the other, or finally two fragments of high similarity, each from one the sequences, are paired.
Machine Learning and Deep Learning for biomedical image analysis.Dr. Simone Bonechi, Univ. di Siena
The tutorial will introduce the fundamental concepts behind Deep Learning and Machine Learning, with particular attention to their relevance for the analysis of biomedical images. In this context we will also discuss the main challenges that need to be addressed in the application of these techniques in the biomedical domain. In particular, we will explore various applications that demonstrate how to manage data scarcity and how to integrate explainability tools into the automated analysis pipeline.
Computational Methods for Sequencing Technologies in Cancer Genomics.Dr. Romina D'Aurizio, IIT-CNR
This tutorial provides an overview of computational methods used in the analysis of sequencing data generated from cancer genomics studies. We will cover the peculiarity of different sequencing technologies, data processing, and analysis approaches, with a focus on applications in cancer research. Through hands-on examples and case studies, participants will have a deeper understanding of the role of computational methods in advancing our understanding of cancer genomics.
A computational trip to reveal the last frontiers in the target/drug discovery fieldDr. Alfonso Trezza, Univ. di Siena
In recent years enormous progress has been made in the field of computational biochemistry, from the analysis of primary structures to the reconstruction ex novo of three-dimensional structures of biological systems. These achievements have contributed to the development of new bioinformatics techniques aimed at different purposes. Here, we will embark in a computational trip to reveal the latest bioinformatics frontiers that can identify potential compounds active against a biological target by having a protein primary structure as a starting point.
|Opening of BH10Local Organizing Committee
|De novo sequencing antibodies by Mass-Spectrometry based proteomicsGianibbi Beatrice (UNISI)
|PathLay: a novel graphical server for -omics integration and interpretationLorenzo Casbarra (UNIFI)
|A Graphical Framework for the analysis of Reaction System ProcessesLinda Brodo (UNISS)
|Comprehensive Investigation of BRAF Isoform-Specific Expression: Analyzing the Expression Profiles of BRAF Reference and X1 Transcripts in Melanoma and Beyond using RNA-seq AnalysisMaurizio S. Podda (UNISS)
|Exploring Quantum kernel methods for breast cancer subtyping: a real-world experimentValeria Repetto (VNR)
|COTAN v2: A Comprehensive and Versatile Framework for Single-Cell Gene Co-Expression Studies and Cell Type IdentificationSilvia Giulia Galfre'
|Towards an Accurate and Automated Prediction of the Quality of Radiotherapy Treatments through Dosiomic Features and Plan Complexity MetricsTommaso Zoppi (UNIFI)
|Phylogeny reconstruction via extended BWTVeronica Guerrini (UNIPI)
|Accurate Prediction of Breast Cancer Survival through Coherent Voting Networks with Gene Expression ProfilingMarco Pellegrini (CNR)
|Enhancing Embedding Representations of Biomedical Data using Logic Knowledge in AICaterina Graziani (UNISI)
|Distress prediction based on Penne's bio-heat equation: a Physics Informed Neural Network approachGiuseppe Alessio D'Inverno (UNISI)
|Bioinformatics validation of Fluorescence Lifetime Imaging Microscopy as an informative tool in glioblastoma treatment: a blended transcriptomic and machine learning approachAldo Pastore (SNS)
|HAGRID: a Hybrid Autoencoder with Generative, Recurrent and Iterative DesignFilippo Costanti (UNISI)
|Decoding Protein Functions: Leveraging Graph Neural Networks and Integrated Data for PredictionAlessia Prete (UNISI, TLS)
|Interventi su Biotecnopolo, Aziende TLS, problemi di formazione e ricerca: discussione e considerazioni finaliPanellist confermati Claudia Sala (Mad Lab, TLS), Giuseppe Maccari (DASCH Lab, TLS), Andrea Paolini (Dg, TLS), Roberto Giorgi (Unisi)