A5007407500- Complex Network Analysis Techniques
- Bioinformatics and Genomic Networks
- Complex Systems and Time Series Analysis
- Theoretical and Computational Physics
- Opinion Dynamics and Social Influence
- Evolutionary Game Theory and Cooperation
- scientometrics and bibliometrics research
- Genetics, Aging, and Longevity in Model Organisms
- Computational Drug Discovery Methods
- Microbial Metabolic Engineering and Bioproduction
- Statistical Mechanics and Entropy
- Human Mobility and Location-Based Analysis
- Advanced Graph Neural Networks
- Metabolomics and Mass Spectrometry Studies
- Mental Health Research Topics
- Environmental Impact and Sustainability
- Plant and animal studies
- Neural Networks and Applications
- Gene Regulatory Network Analysis
- Evolution and Genetic Dynamics
- Reservoir Engineering and Simulation Methods
- Gaussian Processes and Bayesian Inference
- Material Dynamics and Properties
- Geographic Information Systems Studies
- Model Reduction and Neural Networks
Universitat Rovira i Virgili
2016-2025
Institució Catalana de Recerca i Estudis Avançats
2025
Consorci Institut D'Investigacions Biomediques August Pi I Sunyer
2022
Northwestern University
2005-2016
Observatori de l'Ebre
2015
Universitat de les Illes Balears
2010
Universidade Federal de Minas Gerais
2006
Universitat de Barcelona
1998-2003
Service de Physique de l'État Condensé
2001
Clínica Diagonal
2001
The mechanisms by which modularity emerges in complex networks are not well understood but recent reports have suggested that may arise from evolutionary selection. We show finding the of a network is analogous to ground-state energy spin system. Moreover, we demonstrate that, due fluctuations, stochastic models give rise modular networks. Specifically, both numerically and analytically random graphs scale-free modularity. argue this fact must be taken into consideration define statistically...
Network analysis is currently used in a myriad of contexts: from identifying potential drug targets to predicting the spread epidemics and designing vaccination strategies, finding friends uncovering criminal activity. Despite promise network approach, reliability data source great concern all fields where complex networks are studied. Here, we present general mathematical computational framework deal with problem networks. In particular, able reliably identify both missing spurious...
Extracting understanding from the growing “sea” of biological and socioeconomic data is one most pressing scientific challenges facing us. Here, we introduce validate an unsupervised method for extracting hierarchical organization complex biological, social, technological networks. We define ensemble hierarchically nested random graphs, which use to method. then apply our real-world networks, including air-transportation network, electronic circuit, e-mail exchange metabolic Our analysis...
Modularity is one of the most prominent properties real-world complex networks. Here, we address issue module identification in two important classes networks: bipartite networks and directed unipartite Nodes are divided into nonoverlapping sets, links must have end node from each set. Directed only type node, but an origin end. We show that can be conveniently represented as for purposes. report on approach especially suited detection networks, define a set random enable us to validate approach.
Many studies demonstrate that there is still a significant gender bias, especially at higher career levels, in many areas including science, technology, engineering, and mathematics (STEM). We investigated field-dependent, gender-specific effects of the selective pressures individuals experience as they pursue academia within seven STEM disciplines. built unique database comprises 437,787 publications authored by 4,292 faculty members top United States research universities. Our analyses...
Abstract The 2021 Nobel Prize in Physics recognized the fundamental role of complex systems natural sciences. In order to celebrate this milestone, editorial presents point view board JPhys Complexity on achievements, challenges, and future prospects field. To distinguish voice opinion each editor, consists a series editor perspectives reflections few selected themes. A comprehensive multi-faceted field complexity science emerges. We hope trust that open discussion will be inspiration for...
Abstract Can we help predict the future impact of researchers using early-career factors? We analyze factors world’s 100 most prominent across 8 scientific fields and identify four key drivers in researchers’ initial career: working at a top 25 ranked university, publishing paper 5 journal, papers quartile (high-impact) journals co-authoring with other their field. find that over 95% multiple had least one these features first years career. scientists who an early career advantage terms...
A large entropy variation (magnetocaloric effect) has been discovered in ceramic perovskites with the formulas La0.65Ca0.35Ti1−xMnxO3−z and La0.5+x+yLi0.5−3yTi1−3xMn3xO3−z. Both Curie temperature change were studied from 4.2 to 400 K for different stoichiometric compositions applied magnetic fields. Our conclusion is that these materials are excellent candidates working refrigeration liquefaction devices a wide range.
Studies of ecological networks (the web interactions between species in a community) demonstrate an intricate link community's structure and its long-term viability. It remains unclear, however, how much persistence depends on the identities present, or role played by each varies as function community which it is found. We measured species' roles studying are embedded within overall network subsequent dynamic implications. Using data from 32 empirical food webs, we find that importance...
The rise of electronic publishing, preprint archives, blogs, and wikis is raising concerns among publishers, editors, scientists about the present day relevance academic journals traditional peer review. These are especially fuelled by ability search engines to automatically identify sort information. It appears that can only remain relevant if acceptance research for publication within a journal allows readers infer immediate, reliable information on value research.Here, we systematically...
The response of an ecosystem to perturbations is mediated by both antagonistic and facilitative interactions between species. It thought that a community's resilience depends crucially on the food web--the network trophic interactions--and web's degree compartmentalization. Despite its ecological importance, compartmentalization mechanisms give rise it remain poorly understood. Here we investigate several definitions compartments, propose ways understand meaning these definitions, quantify...
Collaboration plays an increasingly important role in promoting research productivity and impact. What remains unclear is whether female male researchers science, technology, engineering, mathematical (STEM) disciplines differ their collaboration propensity. Here, we report on empirical analysis of the complete publication records 3,980 faculty members six STEM at select U.S. universities. We find that have significantly fewer distinct co-authors over careers than males, but this difference...
In complex systems, the network of interactions we observe between systems components is aggregate that occur through different mechanisms or layers. Recent studies reveal existence multiple interaction layers can have a dramatic impact in dynamical processes occurring on these systems. However, assume each one are known, while typically for real-world do not information. Here, address issue uncovering from data by introducing multilayer stochastic block models (SBMs), generalization...
Closed-form, interpretable mathematical models have been instrumental for advancing our understanding of the world; with data revolution, we may now be in a position to uncover new such many systems from physics social sciences. However, deal increasing amounts data, need "machine scientists" that are able extract these automatically data. Here, introduce Bayesian machine scientist, which establishes plausibility using explicit approximations exact marginal posterior over and its prior...
Abstract Scientists collaborate through intricate networks, which impact the quality and scope of their research. At same time, funding institutional arrangements, as well scientific political cultures, affect structure collaboration networks. Since such arrangements cultures differ across regions in world systematic ways, we surmise that networks should also systematically regions. To test this, compare among prominent researchers North America Europe. We find Europe establish denser...
A central issue in evaluative bibliometrics is the characterization of citation distribution papers scientific literature. Here, we perform a large-scale empirical analysis journals from every field Thomson Reuters' Web Science database. We find that only 30 2,184 have distributions are inconsistent with discrete lognormal at rejection threshold controls False Discovery Rate 0.05. large, multidisciplinary over-represented this set journals, leading us to conclude that, within discipline,...
Abstract Motivation The analysis of biological samples in untargeted metabolomic studies using LC-MS yields tens thousands ion signals. Annotating these features is the utmost importance for answering questions as fundamental as, e.g. how many metabolites are there a given sample. Results Here, we introduce CliqueMS, new algorithm annotating in-source LC-MS1 data. CliqueMS based on similarity between coelution profiles and therefore, opposed to most methods, allows annotation single...
Given a finite and noisy dataset generated with closed-form mathematical model, when is it possible to learn the true generating model from data alone? This question we investigate here. We show that this model-learning problem displays transition low-noise phase in which can be learned, observation noise too high for learned by any method. Both high-noise phase, probabilistic selection leads optimal generalization unseen data. contrast standard machine learning approaches, including...
Characterizing interactions between drugs is important to avoid potentially harmful combinations, reduce off-target effects of treatments and fight antibiotic resistant pathogens, among others. Here we present a network inference algorithm predict uncharacterized drug-drug interactions. Our takes, as its only input, sets previously reported interactions, does not require any pharmacological or biochemical information about the drugs, their targets mechanisms action. Because models use are...
A principled approach to understand network structures is formulate generative models. Given a collection of models, however, an outstanding key task determine which one provides more accurate description the at hand, discounting statistical fluctuations. This problem can be approached using two criteria that first may seem equivalent: selecting most plausible model in terms its posterior probability; or with highest predictive performance identifying missing links. Here we show while these...
Structural annotation of metabolites relies mainly on tandem mass spectrometry (MS/MS) analysis. However, approximately 90% the known reported in metabolomic databases do not have annotated spectral data from standards. This situation has fostered development computational tools that predict fragmentation patterns silico and compare these to experimental MS/MS spectra. because such methods require molecular structure detected compound be available for algorithm, identification novel...