Programpunkter
Konferensen på Vitalis 2023 består av flera spår med paneldiskussioner, keynote-presentationer och studiosamtal. Större delen av innehållet kommer också göras tillgängligt digitalt via livesändningar och inspelade föreläsningar, tillgängliga on demand.
Sök enkelt i programmet
Du kan välja att söka på ämne, föreläsningstyp, målgrupp eller tid för att enkelt hitta det du är intresserad av genom att klicka på knappen "Fler sökalternativ".
Du kan också välja något av de tematiska spåren med föreläsningar som håller en röd tråd.
Ett tredjesätt är att klicka på knappen Schema för visa en översikt av föreläsningarna per föreläsningssal.
Registrera dig till konferensen | Vitalis
Spår: MIE: Bioinformatics
Alla programpunkterDifferential Gene Expression Data Analysis of ASD using Random Forest
Tikaram, Pragya p, Praveen Kumar Govarthan, Sudip Mukherjee
Tisdag 23 maj 2023 10:45 - 11:00 G1
MIE: Bioinformatics, English, Förinspelat + På plats, Presentation, Verktyg för implementering, Avancerad, Forskare (även studerande), Studerande, Vårdpersonal, Nytta/effekt, Innovativ/forskning
Autism spectrum disorder (ASD) is a developmental disability caused by differences in the brain regions. Analysis of differential expression (DE) of transcriptomic data allows for genome-wide analysis of gene expression changes related to ASD. De-novo mutations may play a vital role in ASD, but the list of genes involved is still far from complete. Differentially expressed genes (DEGs) are treated as candidate biomarkers and a small set of DEGs might be identified as biomarkers using either biological knowledge or data-driven approaches like machine learning and statistical analysis. In this study, we employed a machine learning-based approach to identify the differential gene expression between ASD and Typical Development (TD). The gene expression data of 15 ASD and 15 TD were obtained from NCBI GEO database. Initially, we extracted the data and used a standard pipeline to preprocess the data. Further, Random Forest (RF) was used to discriminate genes between ASD and TD. We identified the top 10 prominent differential genes and compared them with the statistical test results. Our results show that the proposed RF model yields 5-fold cross-validation accuracy, sensitivity and specificity of 96.67%. Further, we obtained precision and F-measure scores of 97.5% and 96.57%, respectively. Moreover, we found 34 unique DEG chromosomal locations having influential contributions in identifying ASD from TD. We have also identified chr3:113322718-113322659 as the most significant contributing chromosomal location in discriminating ASD and TD. Our machine learning-based method of refining DE analysis is promising for finding biomarkers from gene expression profiles and prioritizing DEGs. Moreover, our study reported top-10 gene signatures for ASD may facilitate the development of reliable diagnosis and prognosis biomarkers for screening ASD.Keywords: Gene expression data, NCBI, Autism Spectrum Disorder, Random Forest, Statistical test
OmicSDK-transcriptomics: A web platform for Transcriptomics Data Analysis
AURORA MARIA SUCRE
Tisdag 23 maj 2023 10:30 - 10:45 G1
MIE: Bioinformatics, English, Enbart på plats, Presentation, Avancerad
Towards a Digital Twin in Human Brain: Brain Tumor Detection using K-means
Anastasios Sarris, Panagiotis Bamidis
Tisdag 23 maj 2023 11:00 - 11:15 G1
MIE: Bioinformatics, English, Enbart på plats, Presentation, Avancerad
This presentation is about our work on a brain tumor detection using clustering methods. The ultimate goal is to use this process in a Digital Twin prototype
Challenges of estimating global feature importance in real-world health care data
Aniek Markus
Tisdag 23 maj 2023 11:15 - 11:30 G1
MIE: Bioinformatics, English, Enbart på plats, Presentation, Avancerad
Improving patient similarity using different modalities of phenotypes extracted from clinical narratives
XIAOYI CHEN
Tisdag 23 maj 2023 10:15 - 10:30 G1
MIE: Bioinformatics, English, Enbart på plats, Presentation, Avancerad
How Good is ChatGPT for Medication Evidence Synthesis?
Chunhua Weng
Tisdag 23 maj 2023 11:30 - 11:45 G1
MIE: Bioinformatics, English, Enbart på plats, Presentation, Avancerad