Iddo Friedberg

MS, Ph.D.
Associate Professor
2118 Vet Med
Research Focus & Interests  


I am interested in the large scale analyses of proteins, genomes and metagenomes.

Metagenomics is the study of genomic material extracted directly from the environment. New sequencing technologies have enabled the study of whole populations of genomes taken from microbial communities in the field, as opposed to single species clonal cultures in the lab. Metagenomics offers a way to study how genomes evolve to cope with the microbial biotic and abiotic environments. Our lab helped developed a method to study the correlation between the human gut microbiota and gut gene expression. We are applying this method towards studying infant gut development the effect of gut microbes on human health and wellness.

Bacterial Genome Evolution: Gene blocks are a common occurrence in bacteria: these are genes which lie close together on the chromosome, and may participate in a common cellular or biochemical function. Operons are gene blocks whose member genes are co-transcribed. We have developed a new method to describe the evolution of operons and gene blocks in bacteria. We describe a small set of evolutionary events that can take place in gene block evolution, and count these events to create a new type of molecular clock that tells us how fast or how slow certain gene blocks may have evolved. We hope to learn how new funcitons are acquired by ensembles of genes such as these.

Function Prediction: genomics, proteomics and various other ``-omics'' inundate us with sequence and structure information, but the biological functions of those proteins in many cases still eludes us. Computational prediction of protein and gene function is a rapidly growing research field in bioinformatics [4]. I am the co-organizer of the automated computational protein function prediction meetings: AFP. The AFP meetings bring together researchers to discuss various methods for protein function prediction. My personal interest in function prediction lies in predicting function from protein structure [5]. We have recently started work on predicting gene function based on its genomic context in bacteria, using both genomic and metagenomic data towards that end.

For professional opportunities, and for more information, see my website.

Selected Publications  

Full publication list on PubMedGoogle Scholar


  • Morton JT, Freed SD, Lee SW, and Friedberg I A large scale prediction of bacteriocin gene blocks suggests a wide functional spectrum for bacteriocins BMC Bioinformatics 16:381
  • Pope WH, Bowman CA, Russell DA et al. Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity. Elife 4:e06416 [Elife]
  • Ream DC, Bankapur AR, Friedberg I An Event-Driven Approach for Studying Gene Block Evolution in Bacteria Bioinformatics pii:btv128 [OUP]
  • Friedberg I, Wass M, Mooney SD, Radivojac P Ten Simple Rules for a Community Computational Challenge PLoS Comp Biol 11(4):e1004150 [PLoS]


  • Jiang Y, Clark WT, Friedberg I, Radivojac P The impact of incomplete knowledge on the evaluation of protein function prediction: a structured-output learning perspective Bioinformatics 30(17):i609-16 [PubMed]
  • Wass M, Mooney S, Linial M, Radivojac P, Friedberg I The Automated Function Prediction SIG Looks Back at 2013 and Prepares for 2014.Bioinformatics [PubMed]


  • Ream DC, Murakami ST, Schmidt EE, Huang GH, Liang C, Friedberg I and Cheng XW Comparative analysis of error-prone replication mononucleotide repeats  across baculovirus genomes (2013) Virus Research 178(2):217-25 [PubMed]
  • Schnoes AM, Ream DC, Thorman AW, Babbitt PC, Friedberg I Biases in the Experimental Annotations of Protein Function and their Effect on Our Understanding of Protein Function Space. PLoS Computational Biology PLoS
  • Oberlin AT, Jurkovic DA, Balish MF, Friedberg I Biological Database of Images and Genomes: tools for community annotations linking image and genomic information (2013) Database OUP
  • Radivojac P, Clark WT, Oron TR, Schnoes AM, ..., Bairoch A, Linial M, Babbitt PC, Brenner SE, Orengo C, Rost B, Mooney SD, Friedberg I. A large-scale evaluation of computational protein function prediction methods Nature Methods NPG


  • Donovan SM, Wang M, Li M, Friedberg I, Schwartz SL, Chapkin RS. Host-microbe interactions in the neonatal intestine: role of human milk oligosaccharides. Adv Nutr. 2012 May 1;3(3):450S-5S. doi: 10.3945/an.112.001859.PubMed.
  • Schwartz S, Friedberg I, Ivanov IV, Davidson LA, Goldsby JS, Dahl DB, Herman D, Wang M, Donovan SM, Chapkin RS. A metagenomic study of diet-dependent interaction between gut microbiota and host in infants reveals differences in immune response. Genome Biol. 2012 Apr 30;13(4):r32. PubMed


  • Bielewicz S, Bell E, Kong W, Friedberg I, Priscu JC, Morgan-Kiss RM. Protist diversity in a permanently ice-covered Antarctic lake during the polar night transition. ISME J. 2011 Sep;5(9):1559-64. Mar 10.PubMed


  • Kelly RJ, Vincent DE, Friedberg I. IPRStats: visualization of the functional potential of an InterProScan run. BMC Bioinformatics. 2010 Dec 21;11 Suppl 1.S13.PubMed
  • Wooley JC, Godzik A, Friedberg I. A primer on metagenomics. PLoS Comput Biol. 2010 Feb 26;6(2):e1000667. PubMed