Bromberg Lab

Decoding the blueprint of Life

Modern biology increasingly relies on high-throughput techniques. This trend challenges computational biologists to quickly extract as much useful information from the data as possible. In the genomic sense, this primarily implies correlating phenotypic differences with observed nucleotide sequence variations. On the protein side the challenge generally is to annotate protein function at reasonable accuracy levels. The whole organism level, then incorporates all types of evidence to annotate evolutionary history, current health conditions, and prognosed phenotypic changes.

We believe that nucleic and amino acid sequences contain a large portion of the information necessary to address both of these directions. However, we are always willing to supplement this data with other sources available for computational access. The main interest of this lab is in developing fast, accurate, and meaningful ways of analyzing the growing deluge of biological data and in bringing these developments bench- (or patient-) side. To make our predictions we rely on a number of sequence-based features (including evolutionary information, predicted structural features, and available annotations) and utilize a variety of computational methodologies (including artificial learning, network analysis and statistical methods).

Active projects and services in the lab can be explored here.

We are always looking for interested/qualified individuals to join our team!

Jobs

We have open positions!

Two post-doctoral positions are immediately available in the lab of Dr. Yana Bromberg, in the departments of Biology and Computer Science, Emory University, Atlanta (possibly joint with the Institute of Advanced Studies, Technical University of Munich).

We are seeking highly motivated scholars to continue training in an exciting research laboratory at Emory with a focus on molecular functionality encoded in genome and metagenome data. The Bromberg lab is purely computational, studying interactions between the host and the microbiome in light of health and disease. We are also exploring biotic molecular functionality at the origins of life.

Applicants must hold a Ph.D. in Computational Biology, Bioinformatics, or related fields. Programming skills are essential, as well as some familiarity with the major bioinformatics tools/databases. Experience with high performance computing, machine learning, and whole genome and metagenome analysis is highly desired, but not required.

Interested persons should e-mail a cover letter and C.V. to Dr. Yana Bromberg at yana@bromberglab.org. Please visit http://bromberglab.org for more information

updated: 09/2022

Principal Investigator

Dr. Yana Bromberg’s research focuses on deciphering the DNA “blueprints” of life’s molecular machinery. She develops novel bioinformatics techniques to find out where this machinery comes from and why/how it runs. The answers to these basic questions are important for improving our health/quality of life, preserving our environment, and, well… did we really start as green slime?!

Dr. Bromberg received her degrees from SUNY Stony Brook and Columbia University. Her work has been recognized by private and federal agencies, including NASA and NIH. She received an NSF CAREER award and is also a Fellow of the Munich Institute for Advanced Study. Her findings consistently indicate that our world functions via dependencies and interactions at all scales.

Interests
  • Protein Function and Variant Effect Prediction
  • Artificial Intelligence
Education
  • Ph.D. in Biomedical Informatics (Bioinformatics Track), 2007

    Columbia University, New York, NY

  • M.Phil. in Biomedical Informatics, 2004

    Columbia University, New York, NY

  • B.A. Biology / B.Eng. Computer Science (Magna Cum Laude), 2001

    State University of NY (SUNY) at Stony Brook, Stony Brook, NY

Lab

Current Bromberglab members

Researchers

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Henri Chung

Research Scientist

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Jia Liu

PostDoctoral Associate

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M. Clara De Paolis Kaluza

Research Scientist

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Patrick Li

PhD Student

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Prabakaran Ramakrishnan

PostDoctoral Associate

Alumni

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Ariel Aptekmann

PostDoctoral Associate

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Maximilian Miller

PostDoctoral Associate

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Yannick Mahlich

PostDoctoral Associate

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Yanran Wang

PhD Candidate

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Zishuo Zeng

PhD Student

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Chengsheng Zhu

PostDoctoral Associate

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Tatyana Goldberg

PhD Student

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Adrienne Hoarfrost

PostDoctoral Fellow

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Nick Lusskin

Undergraduate Student

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Alexis Faulborn

Undergraduate Student

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Anton Molyboha

PostDoctoral Associate

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Kenneth McGuinness

PostDoctoral Associate

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Yannick Spreen

Visiting Scholar

Projects

Selected projects & web-services

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Life & Earth - Deep Transfer Learning

Life & Earth - Deep Transfer Learning

linking environmental microbes to geochemistry & mineralogy

fuNTRp

fuNTRp

classify protein positions by type based on the expected range of mutational impacts

predicting sSNVs effects

predicting sSNVs effects

machine learning-based classifier to evaluate deleteriousness of synonymous variants

AVA,Dx

AVA,Dx

prediction of individual predisposition to disease x through variation analysis

HFSP

HFSP

homolgy based protein function prediction using the HFSP measure

clubber

clubber

automated cluster load balancing accelerating computational biology workflows

mi-faser

mi-faser

annotate molecular functionality directly from sequencing read data

fusionDB

fusionDB

explore or map new genomes to database of 1,374 bacteria with available metadata

Predict-Protein

Predict-Protein

Docker image of the RostLab PredictProtein pipeline

pEffect

pEffect

identifying type III effectors by homology-based inference and de novo predictions

SNPdbe

SNPdbe

Database of SNP predicted & experimentally derived functional effects

SNAP

SNAP

Evaluation single amino acid substitutions effects on protein function

Contact

  • yana@bromberglab.org
  • 1510 Clifton Road NE, 1001 O. Wayne Rollins Research Center, Atlanta, GA 30322
  • Enter Building, turn right and walk to Room 1001
  • Monday 09:00 to 17:00
    Tuesday 09:00 to 17:00
    Wednesday 09:00 to 17:00
    Thursday 09:00 to 17:00
    Friday 09:00 to 17:00
  • whereby.com