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analytica 2018
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PhD po­si­ti­on (m/f): Long non-co­ding RNA net­work in­fe­rence from spar­se sin­gle-cell RNA-seq da­ta Aufrufe: 74

Art des Jobs Vollzeit
Eingetragen am 10.01.2018
Einsatzort Leipzig

Jobbeschreibung Your tasks:
This PhD project aims at developing approaches for network inference from sparse single cell transcriptomics (scRNA-seq) data with a particular focus on functional long non-coding RNAs (lncRNAs). Functional lncRNAs have previously been selected relying on network interference in bulk RNAseq data using canonical network measures. However, lncRNAs are on average more lowly expressed than mRNAs in bulk sequencing, and therefore more prone to dropout in scRNA-seq than coding transcripts. Correlation network approaches focusing on lncRNAs are thus compromised by sparse data on lncRNA expression and the computation of correlations on vectors containing mainly zeros. The task is to investigate whether how imputation approaches or missing-value invariant correlation estimation approaches can be used to inference of gene regulatory networks in such data.
Qualifikationen Your profile:
- Masters degree in Bioinformatics, Computer Science, Physics, or Applied Mathematics
- Knowledge and expertise in next generation sequencing data analysis is desirable
- Strong background in statistics and R-based statistical computing
- Experience in programming in at least one of the languages C, C++, Perl, Python, R
- Experience in machine learning is desirable
- Ability to work independently and motivated to work in an interdisciplinary team
- Excellent English skills in speech and writing
Firma Helmholtz-Zentrum für Umweltforschung GmbH - UFZ
04318 Leipzig
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