プロフィール詳細

プロジェクトを作成

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Dr. Marco S.に依頼

Denmark

Freelance Expert in bioinformatics and machine learning for life science and precision medicine

プロフィール概要

I lead precision medicine initiatives with expertise in bioinformatics, data science, machine learning, diagnostics, and business strategy. I have a strategic vision for advancing precision medicine. Led the formulation and execution of target and biomarker discovery strategies, implementing cutting-edge tools and services to deepen our understanding of diseases. Successfully applied data science and AI (xAI) in diverse bioinformatics projects, including target identification, biomarker discovery, and genomic medicine. Collaborated with business development teams to position them in the pharmaceutical industry. Possess a Ph.D. from Stockholm University and a Master's degree from the University of Bologna, with a robust background in bioinformatics and machine learning. Extensive experience in applying machine and deep learning algorithms, such as Random Forest, Support Vector Machine, Convolutional Neural Networks, LSTM, Attention Mechanism, and Symbolic Regression. Developed computational models of genetic variants and employed transfer learning methods using high-throughput sequencing data. Additionally, serve as a key member of the Scientific Advisory Board (AI) at Genetoo, guiding and leading the AI department in optimizing laser parameters and enhancing the understanding of bacterial attachment and proliferation on various surfaces and materials.

専門分野

• ★ Machine Learning
• ★ Bioinformatics
• ★ Biomarker Discovery
• ☆ Biomarkers
• ☆ Omics
• ☆ Data Analysis
• ☆ Gene & Protein Expression Analysis
• ☆ Python
• ☆ Drug Discovery

サービス

• Research
• Consulting
• Data & AI
• Product Development

Research Technology Scouting

Consulting Business Strategy Consulting, Healthcare Consulting

Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

Product Development Product Evaluation, Product Validation, Concept Development, Prototyping

職務経験

Director of AI

Genetoo

5月 2020 - 現在

Head of Bioinformatics, Target & Biomarker Discovery

Abzu ApS

11月 2022 - 12月 2023

Scientific Development Lead - Bioinformatics and Machine Learning Specialist

Abzu ApS

4月 2022 - 10月 2022

Senior Bioinformatician

Abzu ApS

8月 2021 - 3月 2022

Postdoctoral Researcher

University of Copenhagen

10月 2019 - 3月 2022

学歴

PhD

Stockholm University

9月 2014 - 9月 2019

Masters of Science

Bologna University

1月 2013 - 6月 2014

Bachelor’s in Biological sciences

L'Aquila University

10月 2007 - 12月 2012

認定資格

• AI Product Manager

  Bertelsmann and Udacity

  10月 2021 - 現在

出版物

JOURNAL ARTICLE

Marco Salvatore, Jonas Elsborg (2023). Using LLMs and Explainable ML to Analyze Biomarkers at Single-Cell Level for Improved Understanding of Diseases . Biomolecules.

Marco Salvatore, Stylianos Bakoulis, Robert Krautz, Nicolas Alcaraz, Robin Andersson(2022). Endogenous retroviruses co-opted as divergently transcribed regulatory elements shape the regulatory landscape of embryonic stem cells . Nucleic Acids Research. Oxford University Press ({OUP})

Marco Salvatore, Jose Juan Almagro Armenteros, Olof Emanuelsson, Ole Winther, Gunnar von Heijne, Arne Elofsson, Henrik Nielsen(2019). Detecting sequence signals in targeting peptides using deep learning . Life Science Alliance. 2. (5). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString e201900429. Life Science Alliance, {LLC}

PREPRINT

Marco Salvatore, Jonas Elsborg (2023). Using LLM Models and Explainable ML to Analyse Biomarkers at Single Cell Level for Improved Understanding of Diseases .

Marco Salvatore, Marc Horlacher, Annalisa Marsico, Ole Winther, Robin Andersson (2022). Transfer learning identifies sequence determinants of regulatory element accessibility .

Marco Salvatore, Niels Johan Christensen, Samuel Demharter, Meera Machado, Lykke Pedersen, Valdemar Stentoft-Hansen, Miquel Triana Iglesias (2022). Identifying interactions in omics data for clinical biomarker discovery using symbolic regression .

Promoter sequence and architecture determine expression variability and confer robustness to genetic variants <head> <META HTTP-EQUIV="Refresh" CONTENT="0;URL=/servlet/useragent"> </head> .

Marco Salvatore, Stylianos Bakoulis, Robert Krautz, Nicolas Alcaraz, Robin Andersson(2021). Endogenous retroviruses co-opted as divergently transcribed regulatory elements shape the regulatory landscape of embryonic stem cells . Cold Spring Harbor Laboratory