Genes Differentially Expressed Across Major Arteries Are Enriched in Endothelial Dysfunction-Related Gene Sets: Implications for Relative Inter-artery Atherosclerosis Risk DOI Creative Commons
Paul A. Brown

Bioinformatics and Biology Insights, Journal Year: 2024, Volume and Issue: 18

Published: Jan. 1, 2024

Atherosclerosis differs across major arteries. Although the biological basis is not fully understood, limited evidence of genetic differences has been documented. This study, therefore, was aimed to identify differentially expressed genes between clinically relevant arteries and investigate their enrichment in endothelial dysfunction-related gene sets. A bioinformatic analysis publicly available gene-level read counts for coronary, aortic, tibial performed. Differential expression conducted with

Language: Английский

Interpreting omics data with pathway enrichment analysis DOI Creative Commons
Kangmei Zhao, Seung Y. Rhee

Trends in Genetics, Journal Year: 2023, Volume and Issue: 39(4), P. 308 - 319

Published: Feb. 6, 2023

Language: Английский

Citations

43

PTMNavigator: interactive visualization of differentially regulated post-translational modifications in cellular signaling pathways DOI Creative Commons
Julian Müller, Florian Bayer, Mathias Wilhelm

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 8, 2025

Abstract Post-translational modifications (PTMs) play pivotal roles in regulating cellular signaling, fine-tuning protein function, and orchestrating complex biological processes. Despite their importance, the lack of comprehensive tools for studying PTMs from a pathway-centric perspective has limited our ability to understand how modulate pathways on molecular level. Here, we present PTMNavigator, tool integrated into ProteomicsDB platform that offers an interactive interface researchers overlay experimental PTM data with pathway diagrams. PTMNavigator provides ~3000 canonical manually curated databases, enabling users modify create custom diagrams tailored data. Additionally, automatically runs kinase enrichment algorithms whose results are directly visualization. This view intricate relationship between signaling pathways. We demonstrate utility by applying it two phosphoproteomics datasets, showing can enhance analysis, visualize drug treatments result discernable flow PTM-driven aid proposing extensions existing By enhancing understanding dynamics facilitating discovery PTM-pathway interactions, advances knowledge biology its implications health disease.

Language: Английский

Citations

2

Eight quick tips for biologically and medically informed machine learning DOI Creative Commons
Luca Oneto, Davide Chicco

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(1), P. e1012711 - e1012711

Published: Jan. 9, 2025

Machine learning has become a powerful tool for computational analysis in the biomedical sciences, with its effectiveness significantly enhanced by integrating domain-specific knowledge. This integration give rise to informed machine learning, contrast studies that lack domain knowledge and treat all variables equally (uninformed learning). While application of bioinformatics health informatics datasets more seamless, likelihood errors also increased. To address this drawback, we present eight guidelines outlining best practices employing methods sciences. These quick tips offer recommendations on various aspects analysis, aiming assist researchers generating robust, explainable, dependable results. Even if originally crafted these simple suggestions novices, believe they are deemed relevant expert as well.

Language: Английский

Citations

2

Potential Adaptive Introgression From Dogs in Iberian Grey Wolves (Canis lupus) DOI Creative Commons
Carlos Sarabia, Isabel Salado, Alberto Fernández‐Gil

et al.

Molecular Ecology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 10, 2025

ABSTRACT Invading species along with increased anthropogenization may lead to hybridization events between wild and closely related domesticates. As a consequence, carry introgressed alleles from domestic species, which is generally assumed yield adverse effects in populations. The opposite evolutionary adaptive introgression, where genes are positively selected the possible but has rarely been documented. Grey wolves ( Canis lupus ) widely distributed across Holarctic frequently coexist their close relative, dog C. familiaris ). Despite ample opportunity, occurs most Here we studied geographically isolated grey of Iberian Peninsula, who have coexisted large population loosely controlled dogs for thousands years human‐modified landscape. We assessed extent impact introgression on current wolf by analysing 150 whole genomes other Eurasian as well originating Europe western Siberia. identified almost no recent small (< 5%) overall ancient ancestry. Using combination single scan statistics ancestry enrichment estimates, positive selection six DAPP1 , NSMCE4A MPPED2 PCDH9 MBTPS1 CDH13 dogs. include functions immune response brain functions, explain some unique behavioural phenotypes such reduced dispersal compared

Language: Английский

Citations

1

Eleven quick tips for data cleaning and feature engineering DOI Creative Commons
Davide Chicco, Luca Oneto, Erica Tavazzi

et al.

PLoS Computational Biology, Journal Year: 2022, Volume and Issue: 18(12), P. e1010718 - e1010718

Published: Dec. 15, 2022

Applying computational statistics or machine learning methods to data is a key component of many scientific studies, in any field, but alone might not be sufficient generate robust and reliable outcomes results. Before applying discovery method, preprocessing steps are necessary prepare the analysis. In this framework, cleaning feature engineering pillars study involving analysis that should adequately designed performed since first phases project. We call "feature" variable describing particular trait person an observation, recorded usually as column dataset. Even if pivotal, these sometimes done poorly inefficiently, especially by beginners unexperienced researchers. For reason, we propose here our quick tips for on how carry out important correctly avoiding common mistakes pitfalls. Although guidelines with bioinformatics health informatics scenarios mind, believe they can more general applied area. therefore target researcher practitioners wanting perform engineering. simple recommendations help researchers scholars better analyses lead, turn, solid discoveries.

Language: Английский

Citations

35

Ten quick tips for avoiding pitfalls in multi-omics data integration analyses DOI Creative Commons
Davide Chicco, Fabio Cumbo, Claudio Angione

et al.

PLoS Computational Biology, Journal Year: 2023, Volume and Issue: 19(7), P. e1011224 - e1011224

Published: July 6, 2023

Data are the most important elements of bioinformatics: Computational analysis bioinformatics data, in fact, can help researchers infer new knowledge about biology, chemistry, biophysics, and sometimes even medicine, influencing treatments therapies for patients. Bioinformatics high-throughput biological data coming from different sources be more helpful, because each these chunks provide alternative, complementary information a specific phenomenon, similar to multiple photos same subject taken angles. In this context, integration gets pivotal role running successful study. last decades, originating proteomics, metabolomics, metagenomics, phenomics, transcriptomics, epigenomics have been labelled -omics as unique name refer them, omics has gained importance all areas. Even if is useful relevant, due its heterogeneity, it not uncommon make mistakes during phases. We therefore decided present ten quick tips perform an correctly, avoiding common we experienced or noticed published studies past. designed our guidelines beginners, by using simple language that (we hope) understood anyone, believe recommendations should into account bioinformaticians performing integration, including experts.

Language: Английский

Citations

19

Ten quick tips for computational analysis of medical images DOI Creative Commons
Davide Chicco, Rakesh Shiradkar

PLoS Computational Biology, Journal Year: 2023, Volume and Issue: 19(1), P. e1010778 - e1010778

Published: Jan. 5, 2023

Medical imaging is a great asset for modern medicine, since it allows physicians to spatially interrogate disease site, resulting in precise intervention diagnosis and treatment, observe particular aspect of patients' conditions that otherwise would not be noticeable. Computational analysis medical images, moreover, can allow the discovery patterns correlations among cohorts patients with same disease, thus suggesting common causes or providing useful information better therapies cures. Machine learning deep applied particular, have produced new, unprecedented results pave way advanced frontiers discoveries. While computational images has become easier, however, possibility make mistakes generate inflated misleading too, hindering reproducibility deployment. In this article, we provide ten quick tips perform avoiding pitfalls noticed multiple studies past. We believe our guidelines, if taken into practice, help computational-medical community scientific research eventually positive impact on lives worldwide.

Language: Английский

Citations

14

A brief survey of tools for genomic regions enrichment analysis DOI Creative Commons
Davide Chicco, Giuseppe Jurman

Frontiers in Bioinformatics, Journal Year: 2022, Volume and Issue: 2

Published: Oct. 26, 2022

Functional enrichment analysis or pathway (PEA) is a bioinformatics technique which identifies the most over-represented biological pathways in list of genes compared to those that would be associated with them by chance. These functions are found on annotated databases such as The Gene Ontology KEGG; more abundant identified through statistical techniques Fisher's exact test. All PEA tools require input. A few tools, however, read lists genomic regions input rather than genes, and first associate these chromosome their corresponding genes. perform procedure called analysis, can useful for detecting related set regions. In this brief survey, we analyze six (BEHST, g:Profiler g:GOSt, GREAT, LOLA, Poly-Enrich, ReactomePA), outlining comparing main features. Our comparison results indicate inclusion data regulatory elements, ChIP-seq, common among could therefore improve results.

Language: Английский

Citations

23

Genes adaptability and NOL6 protein inhibition studies of fabricated flavan-3-ols lead skeleton intended to treat breast carcinoma DOI

S. Mohammed Zaidh,

Kiran Balasaheb Aher, Girija Balasaheb Bhavar

et al.

International Journal of Biological Macromolecules, Journal Year: 2023, Volume and Issue: 258, P. 127661 - 127661

Published: Oct. 26, 2023

Language: Английский

Citations

11

Combined inhibition of EZH2 and CDK4/6 perturbs endoplasmic reticulum-mitochondrial homeostasis and increases antitumor activity against glioblastoma DOI Creative Commons
Thomas Freitag,

Philipp Kaps,

Justus Ramtke

et al.

npj Precision Oncology, Journal Year: 2024, Volume and Issue: 8(1)

Published: July 25, 2024

Abstract Here, we show that combined use of the EZH2 inhibitor GSK126 and CDK4/6 abemaciclib synergistically enhances antitumoral effects in preclinical GBM models. Dual blockade led to HIF1α upregulation CalR translocation, accompanied by massive impairment mitochondrial function. Basal oxygen consumption rate, ATP synthesis, maximal respiration decreased, confirming disrupted endoplasmic reticulum-mitochondrial homeostasis. This was paralleled depolarization UPR sensors PERK, ATF6α, IRE1α. Notably, dual EZH2/CDK4/6 also reduced 3D-spheroid invasion, partially inhibited tumor growth ovo , impaired viability patient-derived organoids. Mechanistically, this due transcriptional changes genes involved mitotic aberrations/spindle assembly ( Rb, PLK1, RRM2, PRC1, CENPF, TPX2 ), histone modification HIST1H1B, HIST1H3G DNA damage/replication stress events TOP2A, ATF4 immuno-oncology DEPDC1 EMT-counterregulation PCDH1 ) a shift stemness profile towards more differentiated state. We propose for further investigation.

Language: Английский

Citations

4