A5013071897- Gene expression and cancer classification
- Artificial Intelligence in Healthcare
- COVID-19 diagnosis using AI
- Single-cell and spatial transcriptomics
- Machine Learning in Healthcare
- Cell Image Analysis Techniques
- Molecular Biology Techniques and Applications
- Gene Regulatory Network Analysis
- MicroRNA in disease regulation
- Radiomics and Machine Learning in Medical Imaging
- Mycobacterium research and diagnosis
- RNA modifications and cancer
- Epigenetics and DNA Methylation
- COVID-19 Clinical Research Studies
- Bioinformatics and Genomic Networks
- Cancer-related molecular mechanisms research
- Cardiac Imaging and Diagnostics
- Long-Term Effects of COVID-19
- Air Quality and Health Impacts
- Digital Imaging for Blood Diseases
- Acute Lymphoblastic Leukemia research
- Birth, Development, and Health
- Chronic Obstructive Pulmonary Disease (COPD) Research
- SARS-CoV-2 and COVID-19 Research
- Mitochondrial Function and Pathology
Silesian University of Technology
2015-2024
Aging | doi:10.18632/aging.203399. Aleksandra Pisarek, Ewelina Pośpiech, Antonia Heidegger, Catarina Xavier, Anna Papież, Danuta Piniewska-Róg, Vivian Kalamara, Ramya Potabattula, Michał Bochenek, Marta Sikora-Polaczek, Aneta Macur, Woźniak, Jarosław Janeczko, Christopher Phillips, Thomas Haaf, Joanna Polańska, Walther Parson, Manfred Kayser, Wojciech Branicki
Nearly half of all cancers are treated with radiotherapy alone or in combination other treatments, where damage to normal tissues is a limiting factor for the treatment. Radiotherapy-induced adverse health effects, mostly importance cancer patients long-term survival, may appear during long time after finishing and depend on patient's radiosensitivity. Currently, there no assay available that can reliably predict individual's response radiotherapy. We profiled two study sets from breast (n =...
In contemporary biological experiments, bias, which interferes with the measurements, requires attentive processing. Important sources of bias in high-throughput experiments are batch effects and diverse methods towards removal have been established. These include various normalization techniques, yet many require knowledge on number batches assignment samples to batches. Only few can deal problem identification effect unknown structure. For this reason, an original algorithm through...
Recent advances in sample preparation and sequencing technology have made it possible to profile the transcriptomes of individual cells using single-cell RNA (scRNA-Seq). Compared bulk RNA-Seq data, data often contain a higher percentage zero reads, mainly due lower depth per cell, which affects mostly measurements low-expression genes. However, discrepancies between platforms are observed regardless expression level. Using four paired datasets with multiple samples each, we investigated...
Previous studies have suggested that exposure to ionizing radiation increases the risk of ischemic heart disease (IHD). The data from Mayak nuclear worker cohort indicated enhanced for IHD incidence. goal this study was elucidate molecular mechanisms radiation-induced by integrating proteomics with a transcriptomics on post mortem cardiac left ventricle samples workers categorized in four dose groups (0 Gy, < 100 mGy, 100–500 > 500 mGy). were newly analysed here, originated label-free...
Large collections of data in studies on cancer such as leukaemia provoke the necessity applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation voluminous MILE gene expression set. Three analyses are accomplished, each gaining deeper understanding processes underlying types and subtypes. First, main disease groups tested differential against healthy control standard case-control study. Here,...
In the DECODE project, data were collected from 3,114 surveys filled by symptomatic patients RT-qPCR tested for SARS-CoV-2 in a single university centre March-September 2020. The population demonstrated balanced sex and age with 759 SARS-CoV-2( +) patients. most discriminative symptoms at early infection stage loss of taste/smell (OR = 3.33, p < 0.0001), body temperature above 38℃ 1.67, muscle aches 1.30, 0.0242), headache 1.27, 0.0405), cough 1.26, 0.0477). Dyspnea was more often reported...
New diseases constantly endanger the lives of populations, and, nowadays, they can spread easily and constitute a global threat. The COVID-19 pandemic has shown that fight against new disease may be difficult, especially at initial stage epidemic, when medical knowledge is not complete symptoms are ambiguous. use machine learning tools help to filter out those sick patients who do need tested for spreading pathogen, in event an overwhelming increase transmission. This work presents screening...
Combining data from experiments on multispecies studies provides invaluable contributions to the understanding of basic disease mechanisms and pathophysiology pathogens crossing species boundaries. The task gene expression analysis, however, is often challenging given annotation inconsistencies in cases small sample sizes due bias caused by batch effects. In this work we aim demonstrate that an alternative approach standard differential analysis single cell RNA-sequencing (scRNA-seq) based...
Abstract The focus of this research is to combine statistical and machine learning tools in application a high-throughput biological data set on ionizing radiation response. analyzed consist two gene expression sets obtained studies radiosensitive radioresistant breast cancer patients undergoing radiotherapy. were similar principle; however, the treatment dose differed. It shown that introducing mathematical adjustments preprocessing, differentiation trend testing, classification, coupled...
Distinguishing COVID-19 from other flu-like illnesses can be difficult due to ambiguous symptoms and still an initial experience of doctors. Whereas, it is crucial filter out those sick patients who do not need tested for SARS-CoV-2 infection, especially in the event overwhelming increase disease. As a part presented research, logistic regression XGBoost classifiers, that allow effective screening COVID-19, were generated. Each methods was tuned achieve assumed acceptable threshold negative...