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| − | __NOTOC__
| + | '''[http://www.hopkinsmedicine.org/news/media/releases/vulnerabilities_in_genomes_dimmer_switches_should_shed_light_on_hundreds_of_complex_diseases Nature Genetics paper on impact of regulatory variants]''' |
| − | <h1>Welcome to the Beer Lab!</h1>
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| − | [[File:Beer_lab_plate_art.jpg]] | + | '''[http://www.newsweek.com/humans-and-mice-are-both-more-similar-and-different-previously-thought-285635 Newsweek article on Mouse ENCODE paper]''' |
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| − | <h3>Research Interests: </h3> The ultimate goal of our research is to understand how genomic DNA sequence specifies gene regulation.
| + | '''[http://www.hopkinsmedicine.org/news/media/releases/scientists_map_mouse_genomes_mission_control_centers Mouse ENCODE Consortium paper in Nature]''' |
| − | We have recently made significant progress in understanding how DNA sequence features control cell-type specific mammalian enhancer activity by using kmer-based SVM machine learning approaches. For details, see:
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| − | * '''[http://www.horizonpress.com/genomeanalysis Mammalian Enhancer Prediction.]''' Lee D, Beer MA. 2014. Genome Analysis: Current Procedures and Applications. Horizon Press (in press)
| + | '''[http://www.bme.jhu.edu/news-events/news-highlights.php?id=412 Beer Lab awarded NIH grant for regulatory contributions to disease. ]''' |
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| − | * '''[http://www.ncbi.nlm.nih.gov/pubmed/23861010 Robust k-mer Frequency Estimation Using Gapped k-mers.]''' Ghandi M, Mohammad-Noori M, and Beer MA. 2013. Journal of Mathematical Biology. (Epub ahead of print)
| + | '''[http://www.bme.jhu.edu/news-events/news-highlights.php?id=360 kmer-SVM Genome Research paper voted Top 10 in Regulatory Genomics.] ''' |
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| − | * '''[http://www.ncbi.nlm.nih.gov/pubmed/23771147 kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic datasets.]''' Fletez-Brant C*, Lee D*, McCallion AS and Beer MA. 2013. Nucleic Acids Research 41: W544–W556.
| + | '''[http://www.hopkinsmedicine.org/institute_basic_biomedical_sciences/news_events/Announcements/2013_04_YID.html Dongwon Lee awarded Young Investigator Day Award.] ''' |
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| − | * '''[http://www.ncbi.nlm.nih.gov/pubmed/23019145 Integration of ChIP-seq and Machine Learning Reveals Enhancers and a Predictive Regulatory Sequence Vocabulary in Melanocytes.]''' Gorkin DU, Lee D, Reed X, Fletez-Brant C, Blessling SL, Loftus SK, Beer MA, Pavan WJ, and McCallion AS. 2012. Genome Research 22:2290-2301.
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| − | * '''[http://www.ncbi.nlm.nih.gov/pubmed/21875935 Discriminative prediction of mammalian enhancers from DNA sequence.]''' Lee D, Karchin R, and Beer MA. 2011. Genome Research 21:2167-2180.
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| − | This work uses functional genomics DNase-seq, ChIP-seq, RNA-seq, and chromatin state data to computationally identify combinations of transcription factor binding sites which operate to define the activity of a set of cell-type specific enhancers. We are currently focused on:
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| − | * improving this methodology by including more diverse constraints and features
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| − | * predicting the impact of SNPs on enhancer activity (delta-SVM) and GWAS disease association
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| − | * experimentally characterizing the predicted impact of regulatory element mutation in mammalian cells
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| − | * systematically determining regulatory elements from ENCODE human and mouse data
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| − | * using the inferred regulatory code to assess common modes of regulatory element evolution and variation
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| − | <h3>[[Lab Members]]</h3>
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| − | <h3>[[Publications]]</h3>
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