Molecular mimicry between viral antigens and host proteins can produce cross-reacting antibodies leading to autoimmunity. The coronavirus SARS-CoV-2 causes COVID-19, a disease curiously resulting in varied symptoms outcomes, ranging from asymptomatic fatal. Autoimmunity due molecular may provide an explanation. Thus, we computationally investigated Spike known epitopes. We discovered hotspots highlight two examples with tentative high autoimmune potential implications for understanding...

Accurate cancer subtype prediction is crucial for personalized medicine. Integrating multi-omics data represents a viable approach to comprehending the intricate pathophysiology of complex diseases like cancer. Conventional machine learning techniques are not ideal analyzing interrelationships among different categories omics data. Numerous models have been suggested using graph-based uncover veiled representations and network formations unique distinct types heighten predictions regarding...

Abstract Lung cancer is a leading cause of cancer-related mortality, with disparities in incidence and outcomes observed across different racial sex groups. Understanding the genetic factors these critical for developing targeted treatment therapies. This study aims to identify both patient-specific cohort-specific biomarker genes that contribute lung health among African American males (AAMs), European (EAMs), females (AAFs), (EAFs). The real-world data highly imbalanced respect race,...

Motivation: Convolutional neural networks (CNNs) offer potential for analyzing non-grid structured data, such as biological array by converting it into image-like formats using principal component analysis (PCA) of pathway genes. However, PCA-derived components (PCs) from the entire dataset capture global variance but fail to extract sub-cohort (class-specific) variances. Consequently, CNNs trained on PCs perform poorly in survival prediction glioblastoma multiforme (GBM), and corresponding...

Long non-coding RNA plays a vital role in changing the expression profiles of various target genes that lead to cancer development. Thus, identifying prognostic lncRNAs related different cancers might help developing therapy. To discover critical can identify origin cancers, we propose use state-of-the-art deep learning algorithm concrete autoencoder (CAE) an unsupervised setting, which efficiently identifies subset most informative features. However, CAE does not reproducible features runs...

Upon infection, foreign antigenic proteins stimulate the host's immune system to produce antibodies targeting pathogen. These bind regions on antigen called epitopes. Structural similarity (molecular mimicry) of epitopes between an infecting pathogen and host or other pathogenic has previously encountered can impact response may lead cross-reactive antibodies. The ability identify potential molecular mimicry in a illuminate effects which are especially important treatment vaccine design....

Assistive technology is quite necessary to establish a two-way communication among deaf, mute and normal people where none of them needs acquire knowledge sign languages. In this paper, we propose novel aid system that assists the deaf communicate independently with no use language. Usually, mute, each other using visual references simple sentences when knows These small talks are mainly based on some contexts or keywords which can be delineated visually. Again these classified syllables for...

Abstract Motivation Epitope-based molecular mimicry occurs when an antibody cross-reacts with two different antigens due to structural and chemical similarities. Molecular between proteins from viruses can lead beneficial cross-protection the antibodies produced by exposure one also react other. On other hand, a protein pathogen human auto-immune disorders if resulting virus end up interacting host proteins. While suggest possible reuse of vaccines developed for pathogens, cross-reaction may...

Summary SARS-CoV-2 causes COVID-19, a disease curiously resulting in varied symptoms and outcomes, ranging from asymptomatic to fatal. Autoimmunity due cross-reacting antibodies molecular mimicry between viral antigens host proteins may provide an explanation. We computationally investigated Spike known epitopes. discovered hotspots highlight two examples with tentative autoimmune potential implications for understanding COVID-19 complications. show that TQLPP motif thrombopoietin shares...

Background: Lung cancer is the leading cause of death compared to other cancers in USA. The overall survival rate lung not satisfactory even though there are cutting-edge treatment methods for cancers. Genomic profiling and biomarker gene identification patients may play a role therapeutics patients. genes identified by most existing (statistical machine learning based) belong whole cohort or population. That why different people with same disease get kind treatment, but results outcomes...

Background: In the United States, African American Males (AAM) have highest lung cancer incidence and mortality rate compared to European (EAM). Cigarette is considered major risk factor for cancer, but smoking alone fails interpret rationale developing between AAM EAM. The higher rates of among occur even though they lower rates, smoke fewer cigarettes per day, are less likely be heavy smokers than Identifying genomic signatures such as key genes that can differentiate cancers EAM will a...

Keyword extraction is a process where text given to the computer and returns set of keywords that recommend topical words phrases from content documents. methods are being applied many areas especially when we extract in area information retrieval. This has particular interest because people retrieve significant based on keywords. Many techniques have been developed for English text(s). But, very few attempts made Bengali keyword as well context learning. paper presents graph-based algorithm...

Background: Aberrant protein glycosylation is a common feature of cancer and contributes to malignant behavior. However, how what extent the cellular glycome involved in development progression still undefined. The primary objective this study conduct insilico identification genes that could reveal signature using expression profiles genomes. There exists list ~500 several molecular categories. This based on hypothesis if cancer, there shortlist their should carry capable differentiating 33...

Long non-coding RNA plays a vital role in changing the expression profiles of various target genes that leads to cancer development. Thus, identifying prognostic lncRNAs related different cancers might help developing therapy. To discover critical can identify origin cancers, we proposed use state-of-the-art deep learning algorithm Concrete Autoencoder (CAE) an unsupervised setting, which efficiently identifies subset most informative features. However, CAE does not reproducible features...

Abstract Integration of multi-omics data holds great promise for understanding the complex biology diseases, particularly Alzheimer’s, Parkinson’s, and cancer. However, integration is challenging due to high dimensionality complexity data. Traditional machine learning methods are not well-suited handling relationships between different types omics Many models were proposed that utilize graph-based extract hidden representations network structures from enhance cancer prediction, patient...

Local interpretation of explainable AI, SHAP (SHapley Additive exPlanations), in disease classification problems offers significant feature scores for each sample, potentially identifying precision medicine targets. Tailoring treatments based on individual genetic and molecular targets can enhance therapeutic outcomes while minimizing side effects. However, the suitability SHAP's local at patient level remains uncertain. It generates different sets patient-specific genes various runs, even...

Abstract Background Lung cancer is the leading cause of death compared to other cancers in USA. The overall survival rate lung not satisfactory even though there are cutting-edge treatment methods for cancers. Genomic profiling and biomarker gene identification patients may play a role therapeutics patients. genes identified by most existing (statistical machine learning based) belong whole cohort or population. That why different people with same disease get kind treatment, but results...

Chronic wound healing is inconsistent on an individual basis, leading to large treatment costs. The effectiveness of any approach typically assessed by visual inspection the wound. Optical imaging technologies have recently been developed objectively assess physiology complement subjective assessment. One such device a low-cost SmartPhone Oxygenation Tool (SPOT), which can measure tissue oxygenation wounds via non-contact and assessing status. varying skin tones impact measurements due...

Abstract Upon infection, foreign antigenic proteins stimulate the host’s immune system to produce antibodies targeting pathogen. These bind regions on antibody called epitopes. Structural similarity (molecular mimicry) of epitopes between an infecting pathogen and host or other pathogenic has previously encountered can impact response may lead cross-reactive antibodies. The ability identify potential molecular mimicry in a illuminate effects which are especially important treatment vaccine...

Get PDF Email Share with Facebook Tweet This Post on reddit LinkedIn Add to CiteULike Mendeley BibSonomy Citation Copy Text K. Kaile, M. Sobhan, A. Mondal, and Godavarty, "Machine learning algorithms classify Fitzpatrick skin types during tissue oxygenation mapping," in Biophotonics Congress: Biomedical Optics 2022 (Translational, Microscopy, OCT, OTS, BRAIN), Technical Digest Series (Optica Publishing Group, 2022), paper JM3A.4. Export BibTex Endnote (RIS) HTML Plain alert Save article

Here the authors sought to use explainable artificial intelligence (XAI) classify breast cancer subtypes within datasets of diagnosed patients. Following three trials they achieved a 95% success rate using XGBoost model.

Gene expression analysis is a critical method for cancer classification, enabling precise diagnoses through the identification of unique molecular signatures associated with various tumors. Identifying cancer-specific genes from gene values enables more tailored and personalized treatment approach. However, high dimensionality mRNA data poses challenges extraction. This research presents comprehensive pipeline designed to accurately identify 33 distinct types their corresponding sets. It...