Publications related to Finding a vocation for validation: taking proteomics beyond association and location

Related publications (31)

Augmenting large language models with chemistry tools

Andres Camilo Marulanda Bran, Carlo Baldassari, Philippe Schwaller, Oliver Tobias Schilter

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

Nature Portfolio2024

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

Data-driven statistical optimization of a groundwater monitoring network

Andrea Rinaldo

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Elsevier2024

A multi-reservoir extruder for time-resolved serial protein crystallography and compound screening at X-ray free-electron lasers

Christoph Bostedt, Camila Bacellar Cases Da Silveira

Serial crystallography at X-ray free-electron lasers (XFELs) permits the determination of radiation-damage free static as well as time-resolved protein structures at room temperature. Efficient sample delivery is a key factor for such experiments. Here, we ...

Nature Portfolio2023

Data-Driven Discovery of Organic Electronic Materials Enabled by Hybrid Top-Down/Bottom-Up Design

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Sergio Vela Llausi, Jacob Terence Blaskovits

The high-throughput exploration and screening of molecules for organic electronics involves either a 'top-down' curation and mining of existing repositories, or a 'bottom-up' assembly of user-defined fragments based on known synthetic templates. Both are t ...

Wiley-V C H Verlag Gmbh2023

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

Daniel Keller

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...

2022

Lightweight HI source finding for next generation radio surveys

Jean-Paul Richard Kneib, Frédéric Courbin, Aymeric Alexandre Galan, Austin Chandler Peel, Emma Elizabeth Tolley, Mark Thomas Sargent

Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

ELSEVIER2022

Interactions of Tris with rutile surfaces and consequences for in vitro bioactivity testing

Paul Bowen, Ulrich Aschauer

Tris(hydroxymethyl)aminomethane (Tris) has been used as the buffer in bioactivity testing for over two decades and has become a standard choice for the scientific community. While it is believed to be non-interacting, the extent of its interactions with ti ...

Elsevier2021

A Pareto Dominance Principle for Data-Driven Optimization

Daniel Kuhn, Tobias Sutter

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

2024

Miniaturized technologies for high-throughput drug screening enzymatic assays and diagnostics - A review

Paul Joseph Dyson

Drug discovery is a complex, multistep process, in which many challenges need to be overcome at each stage, from the discovery of a biomolecular target to the ensuring of the efficacy and safety of a compound in humans. Today's analytical methods allow ten ...

ELSEVIER SCI LTD2020

Development of Photocatalysts towards the Visible-Light driven C-Terminal Bioconjugation of Peptides and Proteins

Marion Marie-Agnès Garreau

If small molecules have led to tremendous progress in curing diseases, new therapeutic agents such as peptides or antibody-drugs conjugates have emerged as a highly promising next generation of pharmaceuticals. As for small molecules, their derivatization ...

EPFL2020

Impairment of Glycolysis-Derived L-Serine Production in Astrocytes Contributes to Cognitive Deficits in Alzheimer's Disease

Graham Knott

Alteration of brain aerobic glycolysis is often observed early in the course of Alzheimer's disease (AD). Whether and how such metabolic dysregulation contributes to both synaptic plasticity and behavioral deficits in AD is not known. Here, we show that th ...

Cell Press2020

Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks

Olivier Sauter, Alessandro Pau

In this paper we lay the groundwork for a robust cross-device comparison of data-driven disruption prediction algorithms on DIII-D and JET tokamaks. In order to consistently carry on a comparative analysis, we define physics-based indicators of disruption ...

TAYLOR & FRANCIS INC2020

Toward catchment hydro-biogeochemical theories

Andrea Rinaldo, Paolo Benettin, Ilja van Meerveld

Headwater catchments are the fundamental units that connect the land to the ocean. Hydrological flow and biogeochemical processes are intricately coupled, yet their respective sciences have progressed without much integration. Reaction kinetic theories tha ...

WILEY2020

Algorithms and flowchart for the design of synthetic biochemical networks

Homa Mohammadi Peyhani

New drugs are needed to assure effective therapies for previously untreated diseases, emerging diseases, and personalized medicine, but the process of drug development is complex, costly, and time-consuming. This is especially problematic considering that ...

EPFL2020

Design and validation of bioorthogonal probes for cellular disease models

Pier Luca D'Alessandro

Well-validated chemical probes enable testing of biological hypotheses, investigation of target tractability and translatability to the clinical phase. Consequently, these important tool compounds play a key role in the drug discovery process. Moreover, th ...

EPFL2019

Percolation and Internet Science

Emanuele Massaro

Percolation, in its most general interpretation, refers to the “flow” of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction–diffusion s ...

2019

Accelerating Data Analysis in Simulation Neuroscience with Big Data Technologies

Felix Schürmann, Judit Planas Carbonell, Fabien Jonathan Delalondre

Important progress in computational sciences has been made possible recently thanks to the increasing computing power of high performance systems. Following this trend, larger scientific studies, like brain tissue simulations, will continue to grow in the ...

Springer International Publishing2018

Efficient User Guidance for Validating Participatory Sensing Data

Quoc Viet Hung Nguyen, Thành Tâm Nguyên

Participatory sensing has become a new data collection paradigm that leverages the wisdom of the crowd for big data applications without spending cost to buy dedicated sensors. It collects data from human sensors by using their own devices such as cell pho ...

ASSOC COMPUTING MACHINERY2019

Deep Learning of Human Perception in Audio Event Classification

Samuel Denys Beuret

In this paper, we introduce our recent studies on human perception in audio event classification. In particular, the pre-trained model VGGish is used as feature extractor to process audio data, and DenseNet is trained by and used as feature extractor for o ...

IEEE2018