Iddo Friedberg

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Associate Professor

Iowa State University

United States

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About

Iddo Friedberg is an Associate Professor at Iowa State University in the United States. His research focuses on machine learning applications in protein function prediction, bacterial functionality, and antimicrobial resistance. Recent articles highlight significant issues such as biases in function annotations and the discovery of genomic islands in bacterial genomes.

Recent Grants

Grant: Close

FunGCAT

Open Date: 2017-06-01

Close Date: 2019-10-01

Grant: Close

Bilateral BBSRC-NSF/BIO Collaborative Research: ABI Development: A Critical Assessment of Protein Function Annotation

Open Date: 2015-09-01

Close Date: 2018-08-01

Grant: Close

ABI Innovation: Analysis of Operon Evolution Using an Event Driven Approach

Open Date: 2012-05-01

Close Date: 2016-04-30

Grant: Close

ABI Innovation: Analysis of Operon Evolution Using an Even Driven Approach

Open Date: 2012-05-01

Close Date: 2016-04-30

Articles (13)

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2025

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2022

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2020

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2020

Collaborators (11)

Valérie de Crécy-Lagard

University of Florida

UNITED STATES

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UNITED STATES

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Raimund Nagel

Leipzig University

GERMANY

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Claus Kadelka

Assistant Professor

Iowa State University

UNITED STATES

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Alexander Monzon

Assistant Professor Tenure-Track (RTT researcher)

University of Padua

ITALY

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Iddo Friedberg

Research Interests

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About

Recent Grants

Articles (13)

A longitudinal analysis of function annotations of the human proteome reveals consistently high biases

Limitations of current machine learning models in predicting enzymatic functions for uncharacterized proteins

Assembling bacterial puzzles: piecing together functions into microbial pathways

CAFA-evaluator: a Python tool for benchmarking ontological classification methods

Discovering genomic islands in unannotated bacterial genomes using sequence embedding

An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species

GOThresher: a program to remove annotation biases from protein function annotation datasets

Learning from the unknown: exploring the range of bacterial functionality

Vertical transmission of attaching and invasive E. coli from the dam to neonatal mice predisposes to more severe colitis following exposure to a colitic insult later in life

The field of protein function prediction as viewed by different domain scientists

Deploying MMEJ using MENdel in precision gene editing applications for gene therapy and functional genomics

Unraveling a Tangled Skein: Evolutionary Analysis of the Bacterial Gibberellin Biosynthetic Operon

Novel antimicrobial peptide discovery using machine learning and biophysical selection of minimal bacteriocin domains

Collaborators (11)

Valérie de Crécy-Lagard

An Phan

Gregory Phillips

Yana Bromberg

Stephen Ekker

Damiano Piovesan

Michael Wannemuehler

Predrag Radivojac

Raimund Nagel

Claus Kadelka

Alexander Monzon

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