Dementia with Lewy Bodies: Genomics, Transcriptomics, and Its Future with Data Science DOI Creative Commons
Thomas R. Goddard, Keeley J. Brookes, Riddhi Sharma

et al.

Cells, Journal Year: 2024, Volume and Issue: 13(3), P. 223 - 223

Published: Jan. 25, 2024

Dementia with Lewy bodies (DLB) is a significant public health issue. It the second most common neurodegenerative dementia and presents severe neuropsychiatric symptoms. Genomic transcriptomic analyses have provided some insight into disease pathology. Variants within SNCA, GBA, APOE, SNCB, MAPT been shown to be associated DLB in repeated genomic studies. Transcriptomic analysis, conducted predominantly on candidate genes, has identified signatures of synuclein aggregation, protein degradation, amyloid deposition, neuroinflammation, mitochondrial dysfunction, upregulation heat-shock proteins DLB. Yet, understanding molecular pathology incomplete. This precipitates current clinical position whereby there are no available disease-modifying treatments or blood-based diagnostic biomarkers. Data science methods potential improve understanding, optimising therapeutic intervention drug development, reduce burden. prediction will facilitate early identification cases timely application future treatments. Transcript-level across entire transcriptome machine learning analysis multi-omic data uncover novel that may provide clues development. review discuss DLB, highlight gaps literature, describe advance field.

Language: Английский

A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level DOI
Minghao Jiang, Shi‐Yan Zhang,

Hongxin Yin

et al.

Briefings in Bioinformatics, Journal Year: 2023, Volume and Issue: 24(3)

Published: April 5, 2023

Abstract RNA alternative splicing, a post-transcriptional stage in eukaryotes, is crucial cellular homeostasis and disease processes. Due to the rapid development of next-generation sequencing (NGS) technology flood NGS data, detection differential splicing from RNA-seq data has become mainstream. A range bioinformatic tools been developed. However, until now, an independent comprehensive comparison available algorithms/tools at event level still lacking. Here, 21 different are subjected systematic evaluation, based on simulated where exact events introduced. We observe immense discrepancies among these tools. SUPPA, DARTS, rMATS LeafCutter outperforme other event-based also examine abilities identify novel events, which shows that most unsuitable for discovering splice sites. To improve overall performance, we present two methodological approaches i.e. low-expression transcript filtering tool-pair combination. Finally, new protocol selecting perform analysis analytical tasks (e.g. precision recall rate) proposed. Under this protocol, analyze distinct landscape DUX4/IGH subgroup B-cell acute lymphoblastic leukemia uncover TCF12. All codes needed reproduce results https://github.com/mhjiang97/Benchmarking_DS.

Language: Английский

Citations

23
Progress in toxicogenomics to protect human health DOI
Matthew J. Meier, Joshua Harrill, Kamin J. Johnson

et al.

Nature Reviews Genetics, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 2, 2024

Language: Английский

Citations

8
Advance computational tools for multiomics data learning DOI
Sheikh Mansoor,

Saira Hamid,

Thai Thanh Tuan

et al.

Biotechnology Advances, Journal Year: 2024, Volume and Issue: 77, P. 108447 - 108447

Published: Sept. 7, 2024

Language: Английский

Citations

8
Advances in long-read single-cell transcriptomics DOI Creative Commons

Pallawi Kumari,

Manmeet Kaur, Kiran Dindhoria

et al.

Human Genetics, Journal Year: 2024, Volume and Issue: 143(9-10), P. 1005 - 1020

Published: May 24, 2024

Abstract Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The protocols developed for long-read sequencing platforms overcome these limitations by enabling characterization of full-length techniques initially suffered from comparatively poor accuracy compared short read scRNA-Seq. However, with improvements accuracy, accessibility, cost efficiency, long-reads gaining popularity field This review details advances scRNA-Seq, an emphasis on library preparation downstream bioinformatics analysis tools.

Language: Английский

Citations

6
Wnt3a/GSK3β/β-catenin Signalling Modulates Doxorubicin-associated Memory Deficits in Breast Cancer DOI
Wen Li, Gan Chen, Sheng Yu

et al.

Molecular Neurobiology, Journal Year: 2024, Volume and Issue: 61(8), P. 5441 - 5458

Published: Jan. 10, 2024

Language: Английский

Citations

5
Biodegradation of polystyrene and systems biology-based approaches to the development of new biocatalysts for plastic degradation DOI

Ye-Bin Kim,

Seongmin Kim, Chungoo Park

et al.

Current Opinion in Systems Biology, Journal Year: 2024, Volume and Issue: 37, P. 100505 - 100505

Published: Jan. 13, 2024

Language: Английский

Citations

5
Acupuncture Extended the Thrombolysis Window by Suppressing Blood–Brain Barrier Disruption and Regulating Autophagy–Apoptosis Balance after Ischemic Stroke DOI Creative Commons
Zhi‐Hui Zhang, Tianliang Lu, Shanshan Li

et al.

Brain Sciences, Journal Year: 2024, Volume and Issue: 14(4), P. 399 - 399

Published: April 19, 2024

Background: Ischemic stroke (IS) is one of the leading causes death and disability worldwide. The narrow therapeutic window (within 4.5 h) severe hemorrhagic potential limits efficacy recombinant tissue type plasminogen activator (rt-PA) intravenous thrombolysis for patients. Xingnao Kaiqiao (XNKQ) acupuncture an integral part traditional Chinese medicine, specifically designed to address acute ischemic by targeting key acupoints such as Shuigou (GV26) Neiguan (PC6). In this study, we explored XNKQ in extending time interrogated molecular mechanisms responsible effect. Methods: effect was evaluated via TTC staining, neuronal score evaluation, transformation assay, H&E staining. RNA sequencing (RNA-seq) technology performed identify targets intervention acupuncture. Evans blue staining transmission electron microscopy were used assess blood–brain barrier (BBB) integrity. Immunofluorescence co-immunoprecipitation evaluate level autophagy apoptosis validate their interactions with BBB endothelial cells. Results: Acupuncture alleviated infarction neurological deficits extended 6 h. RNA-seq revealed 16 predictors intervention, which related suppressing inflammation restoring function blood vessels. Furthermore, suppressed leakage preserved tight junction protein expression. protective associated regulation autophagy–apoptosis balance dissociated Beclin1/Bcl-2 complex, thereby promoting reducing apoptosis. Conclusion: could serve adjunctive therapy rt-PA thrombolysis, aiming extend mitigate ischemia–reperfusion injury. disruption regulating balance, turn IS. These findings provide a rationale further exploration complementary candidate co-administered rt-PA.

Language: Английский

Citations

4
Demystifying the Black Box: A Survey on Explainable Artificial Intelligence (XAI) in Bioinformatics DOI Creative Commons

Aishwarya Budhkar,

Qianqian Song, Jing Su

et al.

Computational and Structural Biotechnology Journal, Journal Year: 2025, Volume and Issue: 27, P. 346 - 359

Published: Jan. 1, 2025

The widespread adoption of Artificial Intelligence (AI) and machine learning (ML) tools across various domains has showcased their remarkable capabilities performance. Black-box AI models raise concerns about decision transparency user confidence. Therefore, explainable (XAI) explainability techniques have rapidly emerged in recent years. This paper aims to review existing works on bioinformatics, with a particular focus omics imaging. We seek analyze the growing demand for XAI identify current approaches, highlight limitations. Our survey emphasizes specific needs both bioinformatics applications users when developing methods we particularly imaging data. analysis reveals significant driven by need confidence decision-making processes. At end survey, provided practical guidelines system developers.

Language: Английский

Citations

0
De la microscopía a la secuenciación genética: La evolución en las técnicas de diagnóstico de la Leucemia Linfoide Aguda DOI

Dayana Fernanda Pico Sánchez,

Daniela Alexandra Rosero Freire

Bionatura journal :, Journal Year: 2025, Volume and Issue: 2(1), P. 1 - 21

Published: Jan. 11, 2025

La Leucemia Linfoide Aguda (LLA) es una enfermedad hematológica muy heterogénea que afecta tanto a niños como adultos, cuyas tasas de curación han incrementado con el pasar los años. Esto se debe la evolución en las técnicas diagnóstico, contribuido realizar detección más temprana y precisa, monitorear LLA reconocer pronóstico. El objetivo del presente artículo proporcionar revisión comprensiva actualizada sobre avances utilizadas para diagnóstico LLA. Se encontró parte resultados dados por convencionales hemograma análisis morfología celular. Sin embargo, estas deben ser complementadas avanzadas cariotipo, Fluorescence in Situ Hybridization (FISH), RT-PCR detectan alteraciones mutaciones nivel molecular. Además otras NGS, que, aunque aún limitan laboratorios investigación siguen brindando información útil. Estos mejorado significativamente identificación subtipos moleculares genéticas, cuales son clave estratificación riesgo pronóstico, no puede dejar atrás convencionales, ya punto partida realización posteriores. Palabras Clave: cariotipo convencional; FISH; hemograma; Aguda; NGS; RT-PCR.

Citations

0
HighDimMixedModels.jl: Robust high-dimensional mixed-effects models across omics data DOI Creative Commons

Evan Gorstein,

Rosa Aghdam, Claudia Solís‐Lemus

et al.

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(1), P. e1012143 - e1012143

Published: Jan. 13, 2025

High-dimensional mixed-effects models are an increasingly important form of regression in which the number covariates rivals or exceeds samples, collected groups clusters. The penalized likelihood approach to fitting these relies on a coordinate descent algorithm that lacks guarantees convergence global optimum. Here, we empirically study behavior this simulated and real examples three types data common modern biology: transcriptome, genome-wide association, microbiome data. Our simulations provide new insights into algorithm’s settings, and, comparing performance two popular penalties, demonstrate smoothly clipped absolute deviation (SCAD) penalty consistently outperforms least shrinkage selection operator (LASSO) terms both variable estimation accuracy across omics To empower researchers biology other fields fit with SCAD penalty, implement Julia package, HighDimMixedModels.jl .

Language: Английский

Citations

0