/2019 Spring Bioinformatics Seminar Schedule
2019 Spring Bioinformatics Seminar Schedule2019-04-10T13:16:57+00:00

2019 Spring Bioinformatics Seminar Schedule

Syllabus and Q/A

  • Sandra Rodriguez Zas
  • Thurs, 2019-01-17 12:00

Bioinformatics Workflow Management & Testing

Predicting Cancer Involvement of genes from heterogenous data

Functional characterization of breast cancer risk variants: an integrative analysis

iGPSe: A visual analytic system for integrative genomic based cancer patient stratification

The transcriptome of zinc deficient maize roots and its relationship to DNA methylation loss

Comparative transcriptome analysis reveals new molecular pathways for cucumber genes related to sex determination

A method for identifying prevalent chemical combinations in the US population

Integration and bioinformatics analysis of DNA-methylated genes associated with drug resistance in ovarian cancer

Part One: Eclidean Distance Analysis; Part Two: Software Dedicated to Virus Sequence Analysis

The poly-omics of ageing through individual-based metabolic modelling

iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE

  • Fisk Undergraduate Student
  • Thurs, 2019-04-04 12:00

The Genetic Overlap Between Hair and Eye Color/Heritability and Genome-Wide Association Studies for Hair Color in a Dutch Twin Family Based Sample

Bioinformatic analysis of whole-genome sequence data

Identifying cancer prognostic modules by module network analysis

BRCA-Pathway: a structural integration and visualization system of TCGA breast cancer data on KEGG pathways

Early-life gut microbiome and egg allergy

A cluster robustness score for identifying cell subpopulations in single cell gene expression datasets from heterogeneous tissues and tumors

KnowEnG: Big Data To Knowledge Center of Excellence
1206, West Gregory Drive, MC 195, Urbana IL, 61801
Email: knoweng@illinois.edu

The KnowEnG BD2K center is supported by grant U54GM114838 awarded by NIGMS through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative.