1 / 4

Integrative Approach to Predict Novel Mitosis-Associated Gene Targets

This study integrates prediction methods to uncover novel gene targets related to mitosis, validated through experimental validation of spindle proteins. Utilizing biological data kernels, the research predicts genes involved in chromosome condensation. Functional predictions related to cell migration using systems biology are explored, focusing on gene relationships associated with drug response in heterogenous tumors. Collaborations with experts in bioinformatics and genetics enhance the analysis of gene ontologies and experimental phenotypes, employing various metrics to measure gene pair similarity in different ontologies. Ongoing work includes investigations with multi-regression analyses and heatmaps to identify genetic expression variations in tumor cell lines.

hanzila
Download Presentation

Integrative Approach to Predict Novel Mitosis-Associated Gene Targets

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Systematicprediction of novel gene targets associatedto mitosis: Integration of predictionmethods Experimental validation Novel spindle proteins Fisher 1) Rojas et al. Uncoveringthe molecular machinery of the human spindle--anintegration of wet and drysystemsbiology. PLoSOne. 2012;7(3):e31813 Kernels Novel Chromos. Conden. Genes 2) Jean-KarimHériché et al. …& Jan Ellenberg. Integration of biological data by kernels on graph nodes allows prediction of genes involved in mitotic chromosome condensation . Submitted.

  2. Functionalprediction of novel genes and gene relationshipsrelatedtocellmigration: 3) Case study: ECM stiffnesseffectsin the MCF10CA1a malignanttumourcellline. Functionalsystemsprediction usingproteinnetworks and kernels Diferentiallyexpressed genes Transcriptomic and proteomic data In collaborationwithStaffanStrömblad.

  3. Methodstoidentifygeneticexpressionvariationassociatedwithdrug response in heterogeneoustumours 1) Tumourlines / taxoltreatment 4) Tumourlinesseparation: Sensitive / Resistant Gene expressionmatrix + Celltypesfrequencymatrix + Multi-regression 3) 2) Sensitive / Resistant Heatmap of theidentified genes Changes in expressiondependantoncelltypes and drugtreatment response In collaborationwithAltschuler & Wulab (UT Southwestern). Manuscript in preparation.

  4. Relationship of genes in differentontologies: Gene Ontology (GO) and experimental phenotypes. Metricstomeasuregene pairssimilarity in differentontologies: Metriccorrelationcomparisonstudies: Semanticsimilarity in GO. • Euclideandistance • StandarizedEuclideandistance • Mahalanobisdistance • City Block metric • Minkowskimetric • Cosinedistance • Correlationdistance • Hammingdistance • HammingModifiedsimilarity • Jaccarddistance • Clusteringdistance • Clusteringsimilarity • TF-IDF similarity Ongoingwork in collaborationwithGabriellaRustici.

More Related