Article
Multidisciplinary Sciences
Samantha Laber, Sara Forcisi, Liz Bentley, Julia Petzold, Franco Moritz, Kirill S. Smirnov, Loubna Al Sadat, Iain Williamson, Sophie Strobel, Thomas Agnew, Shahana Sengupta, Tom Nicol, Harald Grallert, Margit Heier, Julius Honecker, Joffrey Mianne, Lydia Teboul, Rebecca Dumbell, Helen Long, Michelle Simon, Cecilia Lindgren, Wendy A. Bickmore, Hans Hauner, Philippe Schmitt-Kopplin, Melina Claussnitzer, Roger D. Cox
Summary: This study found that variants in FTO are strongly associated with obesity. Through experiments in mice, it was confirmed that the deletion of the conserved cis-regulatory module rs1421085 can affect gene expression and mitochondrial function in adipocytes. The study also showed a cross-species conservation of the regulatory circuitry at molecular, cellular, metabolic, and organismal levels, revealing a previously unknown contextual dependence of the variant's action.
Article
Forestry
Nuria Aquilue, Christian Messier, Kyle T. Martins, Veronique Dumais-Lalonde, Marco Mina
Summary: Forest managers require reliable tools to support planning decisions in the face of global environmental changes, and the functional network approach presents a trait-based method to guide sustainable forest management. By clustering species into functional groups, utilizing forest stands as network nodes, and exchanging functional traits based on species dispersal capacity, the approach allows for evaluation of landscape-level functional diversity, vulnerability, and functional connectivity.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Environmental Studies
Michele Acuto, Benjamin Leffel
Summary: Cities are increasingly formalizing collaborations across borders through city networks, which are underestimated as a wide ecosystem of global partnerships between local authorities. These networks should be seen as an institutionalized form of city governance presenting challenges for cities to expand beyond their local boundaries.
Article
Education & Educational Research
Rahul Pandey, Hemant Purohit, Aditya Johri
Summary: This paper presents and tests a theoretically motivated model to rate videos on their potential to support learning goals. The results show that the model ratings strongly correlate with the expected learning gain of the users.
EDUCATION AND INFORMATION TECHNOLOGIES
(2022)
Article
Biochemical Research Methods
Momo Langenstein, Henning Hermjakob, Manuel Bernal Llinares
Summary: Effective curation tools are important to keep up with the rapid growth of databases and newly published information. A decoupled, modular, and scriptable architecture is proposed to build new curation tools on top of existing platforms, without requiring changes to the existing infrastructure. The flexibility of the proposed design is demonstrated through a case study, showing how it can streamline and enhance curator workflow.
Article
Anthropology
Ryan Federo, Xavier Bustamante
Summary: This article analyzes the global interorganizational network by examining the connections between international actors and explores the impact of the COVID-19 pandemic on this network. The study reveals the fragmented, polycentric, and complex nature of the global interorganizational network and emphasizes the use of media-reported events and the Goldstein scale in understanding the challenging relational dynamics among international actors.
Article
Evolutionary Biology
Yan-Nan Liu, Rong-Mei Chen, Qi-Ting Pu, Lotanna M. Nneji, Yan-Bo Sun
Summary: This study re-analyzed transcriptomic data of chickens and found that transposable elements (TEs) play an important role in adaptive evolution, with their expression changes exceeding genetic changes. These TEs were co-expressed with diverse genes and involved in regulatory activities.
GENOME BIOLOGY AND EVOLUTION
(2022)
Article
Green & Sustainable Science & Technology
Rebeca Utrilla-Catalan, Rocio Rodriguez-Rivero, Viviana Narvaez, Virginia Diaz-Barcos, Maria Blanco, Javier Galeano
Summary: Following the liberalization of the coffee sector, governance and power balance in the international coffee trade has changed, leading to greater inequality between producing and importing countries.
Article
Hematology
Caitlyn Vlasschaert, Taralynn Mack, J. Brett Heimlich, Abhishek Niroula, Md Mesbah Uddin, Joshua Weinstock, Brian Sharber, Alexander J. Silver, Yaomin Xu, Michael Savona, Christopher Gibson, Matthew B. Lanktree, Michael J. Rauh, Benjamin L. Ebert, Pradeep Natarajan, Siddhartha Jaiswal, Alexander G. Bick
Summary: Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related somatic mosaicism associated with significant morbidity and mortality. Differentiating true CHIP mutations from sequencing artifacts and germ line variants is a bioinformatic challenge. We present a stepwise method to improve the accuracy of CHIP calls using filtering, variant annotation, and population-based associations. This high-fidelity call set refines population-based associations of CHIP with incident outcomes and is crucial for clinical diagnostic assays.
Article
Biochemical Research Methods
Anush Chiappino-Pepe, Vassily Hatzimanikatis
Summary: PhenoMapping is a protocol that utilizes GEMs, omics, and phenotypic data to map cellular processes and observed phenotypes, classify genes as conditionally and unconditionally essential, and guide comprehensive curation of GEMs.
Article
Ecology
A. C. Risch, S. Zimmermann, M. Schutz, E. T. Borer, A. A. D. Broadbent, M. C. Caldeira, K. F. Davies, N. Eisenhauer, A. Eskelinen, P. A. Fay, F. Hagedorn, J. M. H. Knops, J. J. Lembrechts, A. S. MacDougall, R. L. McCulley, B. A. Melbourne, J. L. Moore, S. A. Power, E. W. Seabloom, M. L. Silviera, R. Virtanen, L. Yahdjian, R. Ochoa-Hueso
Summary: The microbial metabolic quotient (MMQ) is an important parameter for understanding the microbial regulation of the carbon cycle. The study found that nutrient addition and herbivore exclusion had minimal effects on MMQsoil, while edaphoclimatic variables such as temperature, water holding capacity, and soil organic carbon concentration were the main determinants.
GLOBAL ECOLOGY AND BIOGEOGRAPHY
(2023)
Article
Mathematics, Interdisciplinary Applications
Timothy LaRock, Mengqiao Xu, Tina Eliassi-Rad
Summary: This paper examines liner shipping service route data and develops a path-based methodology for analyzing the data. By computing navigational trajectories and minimizing cargo transfers, this approach provides a better understanding of the structure and centrality measures in the maritime shipping network.
Article
Biodiversity Conservation
Guoli Zhang, Ming Wang, Kai Liu
Summary: This paper compares and analyzes the application of two feedforward neural network models (CNNs and MLPs) in global wildfire susceptibility prediction, and explores the interpretability of the CNNs model. By constructing response variables and monthly wildfire predictors, four MLPs and CNNs architectures were built, and five statistical measures were used to evaluate the prediction performance of the models. The contextual-based CNN-2D model was found to have the highest accuracy, while the MLPs model was more suitable for pixel-based classification, and the performance ranking of the four models was CNN-2D > MLP-1D > MLP-2D > CNN-1D.
ECOLOGICAL INDICATORS
(2021)
Article
Biochemical Research Methods
Bader F. Al-Anzi, Mohammad Khajah, Saja A. Fakhraldeen
Summary: In this study, high-performance multinomial regression models were developed using budding yeast datasets to predict the impact of genetic disruptions on viability. These models are interpretable, provide non-binary predictions, and can predict negative genetic interactions.
Article
Multidisciplinary Sciences
Rebecca L. Kordas, Samraat Pawar, Dimitrios-Georgios Kontopoulos, Guy Woodward, Eoin J. O'Gorman
Summary: Organisms' ability to adjust their physiological response to warming varies with body size, and chronic exposure to higher temperatures increases their sensitivity to acute heat. A mathematical model suggests that metabolic plasticity could amplify energy flux through ecosystems in response to warming, highlighting the importance of considering this factor in predicting global warming impacts on ecosystems.
NATURE COMMUNICATIONS
(2022)
Article
Mathematics, Interdisciplinary Applications
Gael Poux-Medard, Sergio Cobo-Lopez, Jordi Duch, Roger Guimera, Marta Sales-Pardo
Summary: Many studies have shown regularities in human decision-making, but accurately predicting unobserved decisions remains a challenge. The research found that people tend to rely on recent information to guess market trends, and identified a set of strategies used by players that are analogous to behaviors observed in other contexts.
Article
Physics, Multidisciplinary
Oscar Fajardo-Fontiveros, Roger Guimera, Marta Sales-Pardo
Summary: Network inference is the process of learning complex network properties from data. Metadata, including node attributes and other network information, can improve inference in probabilistic network models. This study investigates the impact of metadata on the inference process and finds that the addition of metadata can dramatically change the accuracy of predictions. When data and metadata are correlated, metadata has the most significant contribution to the inference process.
Article
Multidisciplinary Sciences
Manusnan Suriyalaksh, Celia Raimondi, Abraham Mains, Anne Segonds-Pichon, Shahzabe Mukhtar, Sharlene Murdoch, Rebeca Aldunate, Felix Krueger, Roger Guimera, Simon Andrews, Marta Sales-Pardo, Olivia Casanueva
Summary: We designed a wisdom-of-the-crowds GRN inference pipeline coupled with complex network analysis to understand the organizational principles governing gene regulation in long-lived glp-1/Notch Caenorhabdities legans. Through screening 80% of regulators, we discovered 50 new aging genes, with 86% having human orthologues. The core genes essential for longevity, including those involved in insulin-like signaling (ILS), were found, indicating the predictive functionality of the GRN structure.
Article
Computer Science, Artificial Intelligence
Adam R. Pah, David L. Schwartz, Sarath Sanga, Charlotte S. Alexander, Kristian J. Hammond, Luis A. N. Amaral
Summary: To craft effective public policy, governments need to gather data on performance and public responses. While federal administrative agencies and the Congress do this and make the data accessible, the judicial branch is an outlier, as court records are effectively out of reach behind a paywall and technical obstacles. The SCALES OKN aims to address this by transforming the transparency and accessibility of court records, facilitating the development of new AI solutions for the benefit of the judiciary, legal scholars, and the public.
Article
Health Care Sciences & Services
Meagan Bechel, Adam R. Pah, Stephen D. Persell, Curtis H. Weiss, Luis A. Nunes Amaral
Summary: This study proposes a data-driven metric for clinician disease recognition that takes into account the variability in patient disease severity and institutional standards. By evaluating ventilatory management in patients with acute respiratory distress syndrome (ARDS), it was found that training background was associated with physician recognition, with non-PCCM physicians recognizing ARDS cases less frequently but expressing greater satisfaction with obtaining diagnostic information.
BMC MEDICAL RESEARCH METHODOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Daniel Vazquez, Roger Guimera, Marta Sales-Pardo, Gonzalo Guillen-Gosalbez
Summary: Precisely predicting the relationship between countries' energy consumption and pollution levels and socioeconomic drivers is crucial for supporting effective sustainable policy-making. Traditional predictive models based on rigid mathematical expressions with constant elasticities are limited, while a Bayesian approach to symbolic regression can find analytical expressions that outperform traditional models and challenge the assumption of constant elasticities.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2022)
Article
Multidisciplinary Sciences
Weihua Lei, Luiz G. A. Alves, Luis A. Nunes Amaral
Summary: The authors propose a machine learning framework for predicting connections removal in transportation networks and investigate the dynamics of edge removal in the Brazilian domestic bus transportation network and the U.S. domestic air transportation network. They find that machine learning models can accurately predict edge removals on a monthly time scale and even in the presence of external shocks. The authors also demonstrate the usefulness of their approach by forecasting the impact of a hypothetical reduction in the scale of the U.S. air transportation network due to CO2 emissions reduction policies. This forecasting approach could be valuable for future infrastructure planning.
NATURE COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Jenny Liu, Luis A. N. Amaral, Sinan Keten
Summary: A promising approach to study protein dynamics is to represent it using networks and take advantage of well-established methods from network science. Most studies construct protein dynamics networks using correlation measures, which are only applicable under specific conditions. In this study, the researchers applied an inverse approach to build networks based on protein dihedral angles, resulting in physically interpretable and robust networks. By using this method, dynamical differences were identified for proteins with structural similarity. The study demonstrates the importance of using the inverse approach to extract networks from protein dynamics.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
(2023)
Article
Chemistry, Multidisciplinary
Valentina Negri, Daniel Vazquez, Marta Sales-Pardo, Roger Guimera, Gonzalo Guillen-Gosalbez
Summary: This research demonstrates that Bayesian symbolic learning can simplify process modeling tasks, making process models easier to use. Compared to conventional models, this method provides analytical expressions that are easier to communicate and manipulate algebraically.
Article
Mathematics, Interdisciplinary Applications
Lluc Font-Pomarol, Angelo Piga, Rosa Maria Garcia-Teruel, Sergio Nasarre-Aznar, Marta Sales-Pardo, Roger Guimera
Summary: Laws and legal decision-making continuously adapt to new social paradigms, reflecting changes in culture and social norms. Using an information-theoretic approach, we track trends in judicial decisions to identify periods of disruptive topics. Analyzing over 100,000 Spanish court decisions, we detect an abrupt change in housing-related decisions around 2016. Our approach allows us to interpret the results in terms of legislative changes, landmark decisions, and social movements.
Article
Multidisciplinary Sciences
Oscar Fajardo-Fontiveros, Ignasi Reichardt, Harry R. De Los Rios, Jordi Duch, Marta Sales-Pardo, Roger Guimera
Summary: Learning analytical models from noisy data is challenging and depends on the noise level. The authors analyze the transition of the model-learning problem from a low-noise phase to a phase where the noise is too high for the model to be learned. They also estimate upper bounds for the transition noise.
NATURE COMMUNICATIONS
(2023)
Article
Mathematics, Interdisciplinary Applications
Lluis Danus, Carles Muntaner, Alexander Krauss, Marta Sales-Pardo, Roger Guimera
Summary: Scientists collaborate through intricate networks, which are influenced by funding, institutional arrangements, and cultural factors. We compared the collaboration networks of prominent researchers in North America and Europe and found that European researchers have denser networks, while those in North America have more decentralized networks. The impact of publications by North American researchers is significantly higher than that of European researchers, even when collaborating with other prominent researchers.
Article
Cell Biology
Thomas Stoeger, Rogan A. Grant, Alexandra C. McQuattie-Pimentel, Kishore R. Anekalla, Sophia S. Liu, Heliodoro Tejedor-Navarro, Benjamin D. Singer, Hiam Abdala-Valencia, Michael Schwake, Marie-Pier Tetreault, Harris Perlman, William E. Balch, Navdeep S. Chandel, Karen M. Ridge, Jacob Sznajder, Richard Morimoto, Alexander Misharin, G. R. Scott Budinger, Luis A. Nunes Amaral
Summary: The length of transcripts explains the majority of transcriptional changes observed during aging in mice and humans. The relative abundance of long transcripts is lower in aging, and antiaging interventions can counter this length association. Genes with the longest transcripts are associated with lifespan extension, while genes with the shortest transcripts are associated with lifespan shortening.
Article
Multidisciplinary Sciences
Sergio Cobo-Lopez, Vinod K. Gupta, Jaeyun Sung, Roger Guimera, Marta Sales-Pardo
Summary: This study reveals the robust structural patterns underlying the human gut microbiome using whole metagenomic datasets. The taxonomic composition of the gut microbiome is associated with a combination of generalist and specialist species, which play distinct ecological roles. The findings suggest that there is a nested structure within the gut microbiomes of individuals.
Article
Chemistry, Multidisciplinary
Xabier Rodriguez-Martinez, Enrique Pascual-San-Jose, Zhuping Fei, Martin Heeney, Roger Guimera, Mariano Campoy-Quiles
Summary: By training artificial intelligence algorithms with self-consistent datasets, this study found that Bayesian machine scientist and random decision forest methods can effectively predict the photocurrent-composition phase space in organic photovoltaic material systems. The research identified highly predictive models using only material band gaps, simplifying the rationale of the photocurrent-composition space in this field.
ENERGY & ENVIRONMENTAL SCIENCE
(2021)