Article
Multidisciplinary Sciences
Pisanu Buphamalai, Tomislav Kokotovic, Vanja Nagy, Joerg Menche
Summary: Researchers introduced a network approach to evaluate the impact of rare gene defects across biological scales. They constructed a multiplex network and analyzed rare diseases, discovering distinct phenotypic modules that can predict rare disease gene candidates. These findings open up new avenues for applying network-based tools in cross-scale data integration.
NATURE COMMUNICATIONS
(2021)
Article
Multidisciplinary Sciences
Marcin Pilarczyk, Mehdi Fazel-Najafabadi, Michal Kouril, Behrouz Shamsaei, Juozas Vasiliauskas, Wen Niu, Naim Mahi, Lixia Zhang, Nicholas A. Clark, Yan Ren, Shana White, Rashid Karim, Huan Xu, Jacek Biesiada, Mark F. Bennett, Sarah E. Davidson, John F. Reichard, Kurt Roberts, Vasileios Stathias, Amar Koleti, Dusica Vidovic, Daniel J. B. Clarke, Stephan C. Schurer, Avi Ma'ayan, Jarek Meller, Mario Medvedovic
Summary: iLINCS is an integrative web-based platform that integrates multiple omics data types and analysis tools for the analysis and visualization of cellular perturbations and omics data. Its user-friendly interface enables users to perform complex omics signatures analysis and drug repositioning.
NATURE COMMUNICATIONS
(2022)
Article
Gastroenterology & Hepatology
Yichen Yang, Yuequn Ma, Meng Yuan, Yonglin Peng, Zhonghai Fang, Ju Wang
Summary: This study conducted a comprehensive analysis to explore genes, pathways, and disease-specific networks related to hepatocellular carcinoma (HCC). The research identified differentially expressed genes, enriched pathways, disease modules, and hub genes in the HCC-specific subnetwork. Survival analysis revealed a negative correlation between the expression levels of hub genes and the survival rate of HCC patients.
LIVER INTERNATIONAL
(2021)
Article
Biochemistry & Molecular Biology
Zongliang Yue, Eric Zhang, Clark Xu, Sunny Khurana, Nishant Batra, Son Do Hai Deng, James J. Cimino, Jake Y. Chen
Summary: PAGER-CoV is a new web-based database that assists biomedical researchers in interpreting coronavirus-related functional genomic study results using a vast collection of PAGs. By exploring relationships between PAGs, users can gain deeper insights into the research information. This database can help researchers find molecular biology mechanisms and tailored therapeutics for treating COVID-19 patients.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Multidisciplinary Sciences
Md Tauhidul Islam, Lei Xing
Summary: The authors develop a cartography strategy based on gene-gene interactions to transform high-dimensional gene expression data into a spatially configured genomap, enabling accurate deep pattern discovery. This approach presents significant challenges and opportunities in the field of single cell genomics for biomedical research. The unique cartography method captures gene interactions in the spatial configuration of genomaps, allowing for the extraction of deep genomic interaction features and the discovery of discriminative patterns in the data.
NATURE COMMUNICATIONS
(2023)
Review
Neurosciences
Jiawei Wang, Hongyu Zhao, Matthew J. Girgenti
Summary: Gender plays a significant role in the molecular effects of posttraumatic stress disorder (PTSD), with women being more susceptible to PTSD and differences in brain structure between males and females with PTSD. Recent research indicates that dysfunction of GABAergic signaling and immune function predominantly influence the sex-specific molecular determinants of PTSD.
BIOLOGICAL PSYCHIATRY
(2022)
Article
Biochemical Research Methods
Yongsan Yang, Fengcui Qian, Xuecang Li, Yanyu Li, Liwei Zhou, Qiuyu Wang, Xinyuan Zhou, Jian Zhang, Chao Song, Zhengmin Yu, Ting Cui, Chenchen Feng, Jiang Zhu, Desi Shang, Jiaqi Liu, Mengfei Sun, Yuexin Zhang, Huifang Tang, Chunquan Li
Summary: GREAP is a powerful platform for genomic region enrichment analysis, providing comprehensive annotation and enrichment analysis capabilities for genomic regions, along with a customizable genome browser.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Surabhi Jagtap, Abdulkadir Celikkanat, Aurelie Pirayre, Frederique Bidard, Laurent Duval, Fragkiskos D. Malliaros
Summary: This study proposes a novel random walk-based matrix factorization method called BraneMF for learning node representation in a multilayer network and its application to omics data integration. The applicability of learned features for essential multi-omics inference tasks is demonstrated using PPI networks of Saccharomyces cerevisiae, and BraneMF outperforms baseline methods in various downstream tasks.
Article
Biochemical Research Methods
Joel I. Perez-Perri, Marko Noerenberg, Wael Kamel, Caroline E. Lenz, Shabaz Mohammed, Matthias W. Hentze, Alfredo Castello
Summary: Interactions between RNA-binding proteins (RBPs) and RNAs play a critical role in cell biology, and the RNA interactome capture (RIC) method allows for comprehensive and quantitative assessment of these interactions using UV crosslinking, oligo(dT) capture, and proteomics. Recent advancements have enhanced RIC by utilizing LNA probes with stronger binding affinity and SILAC/TMT proteomic techniques, improving RBP quantification accuracy and reproducibility in response to biological cues like metabolic imbalance or virus infection.
Article
Multidisciplinary Sciences
Alex Graudenzi, Davide Maspero, Fabrizio Angaroni, Rocco Piazza, Daniele Ramazzotti
Summary: This study conducted a large-scale analysis of intra-host genomic diversity of SARS-CoV-2, revealing interactions between host-related mutational processes and transmission dynamics, as well as identifying mutational signatures related to nucleotide substitutions. The study also demonstrated the impact of purifying selection on these mutational processes, while some mutations transition towards clonality, increasing overall genomic diversity. Additionally, phylogenomic analysis supported the hypothesis of transmission of minor variants, paving the way for integrated analysis of intra-host genomic diversity and clinical outcomes of SARS-CoV-2 infections.
Article
Biochemical Research Methods
Bertrand Jern Han Wong, Weijia Kong, Hui Peng, Wilson Wen Bin Goh
Summary: Proteomic studies aim to characterize the protein composition of complex biological samples. To address the challenge of low proteome coverage and interpretability, researchers developed PROSE, a fast and scalable pipeline that scores proteins based on gene co-expression network matrices. PROSE shows high accuracy in missing protein prediction and can capture key phenotypic features in proteomics datasets.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Zhitao Mao, Qianqian Yuan, Haoran Li, Yue Zhang, Yuanyuan Huang, Chunhe Yang, Ruoyu Wang, Yongfu Yang, Yalun Wu, Shihui Yang, Xiaoping Liao, Hongwu Ma
Summary: CAVE is a cloud-based platform that integrates calculation, visualization, examination, and correction of metabolic pathways. It can analyze and visualize pathways for over 100 published genome-scale metabolic models or user-uploaded models. CAVE offers model modification functions for users to correct errors in pathway analysis and obtain more reliable pathways.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemical Research Methods
Noriaki Sato, Yoshinori Tamada, Gunagchuang Yu, Yasushi Okuno
Summary: In this study, the researchers developed an R package called CBNplot, which can infer Bayesian networks from gene expression data and visualize and compare enrichment analysis results. The package has the potential to facilitate the study of gene regulatory networks and knowledge discovery in gene expression datasets.
Article
Biochemical Research Methods
Hongjun Chen, Yekai Zhou, Yongjing Liu, Peijing Zhang, Ming Chen
Summary: This study integrated clinical and biomedical research data to systematically mine and analyze pathological proteins and their interaction network in neurodegenerative diseases. It proposed a solution that includes protein isoforms to reveal the impact of protein binding interactions on disease. Finally, a Neurodegenerative Disease Atlas was constructed with interactive 3D molecular graphics.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Multidisciplinary Sciences
Michelle M. M. Kameda-Smith, Helen Zhu, En-Ching Luo, Yujin Suk, Agata Xella, Brian Yee, Chirayu Chokshi, Sansi Xing, Frederick Tan, Raymond G. G. Fox, Ashley A. A. Adile, David Bakhshinyan, Kevin Brown, William D. D. Gwynne, Minomi Subapanditha, Petar Miletic, Daniel Picard, Ian Burns, Jason Moffat, Kamil Paruch, Adam Fleming, Kristin Hope, John P. P. Provias, Marc Remke, Yu Lu, Tannishtha Reya, Chitra Venugopal, Juri Reimand, Robert J. J. Wechsler-Reya, Gene W. W. Yeo, Sheila K. K. Singh
Summary: The RNA-binding protein Musashi-1 (MSI1) has been found to play an essential role in Group 3 (G3) medulloblastoma (MB), and its inhibition can effectively suppress tumor initiation and prolong survival in G3 MB mouse models and patient-derived xenografts. By identifying MSI1 binding targets in normal neural and G3 MB stem cells and cross-referencing them with large-scale screens at different levels, multiple MYC-associated pathways have been discovered to be selectively targeted by MSI1 in G3 MB, providing valuable resources for context-specific therapeutic strategies.
NATURE COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Svetlana Aleshkina, Mikhail Yashkov, Mikhail Salganskii, Vladimir Velmiskin, Alexey Guryanov, Mikhail Bubnov, Mikhail Likhachev
Summary: This study presents a detailed investigation on a novel type of optical fiber for spectral filtering, which utilizes a step-index core with high-index rods embedded into silica cladding. It is experimentally confirmed that this structure can achieve a very sharp stopband and can be used for creating shortpass fiber spectral filters.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Biology
Jordi Martorell-Marugan, Marco Chierici, Giuseppe Jurman, Marta E. Alarcon-Riquelme, Pedro Carmona-Saez
Summary: In this article, the potential of machine learning in the differential diagnosis of systemic lupus erythematosus and primary Sjogren's syndrome using gene expression and methylation data from 651 individuals is demonstrated. The impact of disease heterogeneity on predictive model performance is analyzed, with patients assigned to specific molecular clusters being misclassified more frequently and affecting overall model performance. Additionally, biomarkers that improve predictions compared to using the entire dataset are identified and validated with external studies.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Engineering, Electrical & Electronic
Alexander Vakhrushev, Yan Ososkov, Sergey Alyshev, Aleksandr Khegai, Andrey Umnikov, Fedor Afanasiev, Konstantin Riumkin, Elena Firstova, Alexey Guryanov, Mikhail Melkumov, Sergei Firstov
Summary: The output power characteristics of cladding-pumped lasers based on bismuth-doped phospho- and germanosilicate core glass fibers were studied and analyzed in this article. The developed lasers can provide several hundred milliwatts of output power with a close to 1% slope efficiency. It was found that the Bi-doped germanosilicate fiber laser shows output power saturation, while the Bi-doped phosphosilicate fiber laser does not. The relaxation time of the bismuth active centers (BACs) has a significant impact on the laser efficiency and achieved output power.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2023)
Article
Biochemical Research Methods
Jordi Martorell-Marugan, Marco Chierici, Sara Bandres-Ciga, Giuseppe Jurman, Pedro Carmona-Saez
Summary: This study aims to conduct a comprehensive systematic review of studies applying machine learning to Parkinson's disease data. It summarizes the main advances in using machine learning methodologies for Parkinson's disease research and highlights the increasing interest in this area within the research community.
CURRENT BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Cankut Cubuk, Carlos Loucera, Maria Pena-Chilet, Joaquin Dopazo
Summary: Reprogramming metabolism is a key feature of cancer, and recent research suggests that metabolites may play a crucial role in regulating signaling pathways. Mechanistic models were used to analyze the metabolic and signaling pathway activities of Breast invasive Carcinoma (BRCA), and Gaussian Processes combined with SHapley Additive exPlanations (SHAP) were employed to identify potential causal relationships between metabolite production and signaling pathway regulation. A total of 317 metabolites were found to significantly impact signaling circuits, revealing a complex crosstalk between signaling and metabolic pathways.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Davide Chicco, Giuseppe Jurman
Summary: Although evaluating binary classifications is a common task, there is no consensus on a single statistic for summarizing the confusion matrix. Recent studies have shown that the Matthews correlation coefficient (MCC) outperforms other popular rates in various fields. In this study, the MCC was compared to two other statistics, prevalence threshold (PT) and Fowlkes-Mallows index, and it was found to be more informative in cases where positive and negative data elements are equally important.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Leonid V. V. Kotov, Valery Temyanko, Mikhail M. M. Bubnov, Denis S. S. Lipatov, Alexey S. S. Lobanov, Alexey Abramov, Svetlana S. S. Aleshkina, Alexey N. N. Guryanov, Mikhail E. E. Likhachev
Summary: In this study, high-energy single frequency transform-limited Er-doped amplifiers were pumped by a specially developed Yb-doped fiber laser at 980 nm and a Raman laser at 1480 nm. It was found that pumping at 1480 nm allows achieving slightly higher maximum pulse energy for long pulses in the absence of nonlinear effects. On the other hand, amplifiers with a pump at 980 nm have a higher threshold of stimulated Brillouin scattering (SBS), enabling higher peak power of shorter pulses. Lasers with more than 730 mu J pulse energy and with higher than 3.5 kW peak power were demonstrated.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2023)
Article
Mathematical & Computational Biology
Davide Chicco, Giuseppe Jurman
Summary: Bioinformatics has become an integral part of biomedical research in hospitals worldwide, with the establishment of bioinformatics facilities being a common practice. However, bioinformaticians working in these facilities often lack formal training for their job. To address this, we propose ten simple rules to guide bioinformaticians in providing support to medical doctors, aiming to improve scientific results and foster a productive work environment.
Review
Mathematical & Computational Biology
Davide Chicco, Tiziana Sanavia, Giuseppe Jurman
Summary: Neuroblastoma, a childhood neurological tumor, has a significant impact on the lives of hundreds of thousands of children worldwide. This study focuses on identifying stable genetic signatures for predicting the prognosis of neuroblastoma patients. By analyzing multiple gene expression datasets, we found that the genes AHCY, DPYLS3, and NME1 consistently exhibit prognostic power. These findings highlight the importance of these genes in neuroblastoma prognosis and offer potential avenues for developing better treatments.
Article
Mathematical & Computational Biology
Davide Chicco, Giuseppe Jurman
Summary: Binary classification commonly utilizes machine learning and computational statistics, with ROC AUC serving as the standard metric. However, ROC AUC has flaws and limitations. The Matthews correlation coefficient (MCC) should replace ROC AUC as the standard statistic for binary classification in all scientific studies.
Article
Pharmacology & Pharmacy
Rocio Nunez-Torres, Guillermo Pita, Maria Pena-Chilet, Daniel Lopez-Lopez, Jorge Zamora, Gema Roldan, Belen Herraez, Nuria Alvarez, Maria Rosario Alonso, Joaquin Dopazo, Anna Gonzalez-Neira
Summary: The implementation of pharmacogenetics (PGx) is a significant milestone for achieving safer and more effective therapies in precision medicine. However, the adoption of PGx diagnostics is slow and unequal worldwide, partly due to the lack of ethnic-specific PGx information. Genetic data from 3006 Spanish individuals were analyzed, revealing allele frequencies and putative deleterious variants for main PGx genes. A comparison of high-throughput diagnostic techniques indicated that genotyping with the PGx HT array is the most suitable solution. The integrated information is made available through the Collaborative Spanish Variant Server for the scientific community.
Article
Biology
Pelin Gundogdu, Inmaculada Alamo, Isabel A. Nepomuceno-Chamorro, Joaquin Dopazo, Carlos Loucera
Summary: Single-cell data enables the study of cell dynamics at unprecedented resolution. SigPrimedNet is a data-driven solution that identifies cells and learns the functional summarization of signaling measurements.
Article
Biochemistry & Molecular Biology
Miriam Paya-Milans, Maria Pena-Chilet, Carlos Loucera, Marina Esteban-Medina, Joaquin Dopazo
Summary: Soft tissue sarcoma is a group of rare and difficult-to-treat cancers, and the study shows that computational analysis of gene expression data can reveal the importance of signaling pathways in patient survival. Thirteen signaling circuits were identified as predictors of patient survival, and the protective role of the immune system in the tumor microenvironment and potential therapeutic strategies were also described.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Virology
Carlos Loucera, Rosario Carmona, Marina Esteban-Medina, Gerrit Bostelmann, Dolores Munoyerro-Muniz, Roman Villegas, Maria Pena-Chilet, Joaquin Dopazo
Summary: This study utilized data from the Andalusian Population Health Database to investigate the relationship between prior drug consumption and patient outcomes in COVID-19. It identified 21 drugs associated with better patient survival and effectively controlled covariates.
Article
Biochemistry & Molecular Biology
Javier Perez-Florido, Carlos S. Casimiro-Soriguer, Francisco Ortuno, Jose L. Fernandez-Rueda, Andrea Aguado, Maria Lara, Cristina Riazzo, Manuel A. Rodriguez-Iglesias, Pedro Camacho-Martinez, Laura Merino-Diaz, Inmaculada Pupo-Ledo, Adolfo de Salazar, Laura Vinuela, Ana Fuentes, Natalia Chueca, Federico Garcia, Joaquin A. Dopazo, Jose Lepe
Summary: Recombination is an evolutionary strategy to acquire new viral properties quickly. The Andalusian genomic surveillance strategy has revealed a high number of co-infections, providing an ideal setting for the emergence of new recombinants. Whole genome sequencing of SARS-CoV-2 has been conducted, detecting three novel recombinant variants with two break points. The increased frequency of co-infection and recombination raises the risk of recombinant variants with increased transmissibility and pathogenicity.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)