World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
89
Citations
91915
World Ranking
623
National Ranking
11

Overview

Nir Friedman was affiliated with the Weizmann Institute of Science in Israel. Their research spanned multiple fields, primarily focusing on Medicine and Biochemistry, Genetics and Molecular Biology. Their work delved into several subfields such as Molecular Biology, Oncology, Epidemiology, Cancer Research, and Immunology.

The scientist contributed to research on various main topics, including:

  • Cancer Genomics and Diagnostics
  • Single-cell and spatial transcriptomics
  • Epigenetics and DNA Methylation
  • Liver Disease Diagnosis and Treatment
  • Lung Cancer Research Studies
  • RNA and protein synthesis mechanisms
  • Ubiquitin and proteasome pathways

Nir Friedman published frequently in several scientific venues with notable recurring appearances in bioRxiv (Cold Spring Harbor Laboratory), Nature Biotechnology, Zenodo (CERN European Organization for Nuclear Research), Nature Communications, and the Journal of Hepatology.

Some of their recent scientific papers included the following:

  • ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin, 2021, Nature Biotechnology
  • NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport, 2021, Nature Protocols
  • Extrachromosomal DNA Amplification Contributes to Small Cell Lung Cancer Heterogeneity and Is Associated with Worse Outcomes, 2023, Cancer Discovery
  • Elevated cfDNA after exercise is derived primarily from mature polymorphonuclear neutrophils, with a minor contribution of cardiomyocytes, 2023, Cell Reports Medicine
  • Selective flexible packaging pathways of the segmented genome of influenza A virus, 2020, Nature Communications

The scientist collaborated with a number of frequent co-authors throughout their career. These included Gavriel Fialkoff, Israa Sharkia, Ronen Sadeh, Jenia Gutin, and Alon Chappleboim.

Best Publications

  • Full-length transcriptome assembly from RNA-Seq data without a reference genome.

    Manfred G Grabherr;Brian J Haas;Moran Yassour;Moran Yassour;Joshua Z Levin

  • Probabilistic graphical models : principles and techniques

    Daniel L. Koller;Nir Friedman

  • De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

    Brian J Haas;Alexie Papanicolaou;Moran Yassour;Moran Yassour;Manfred Grabherr

  • Bayesian Network Classifiers

    Nir Friedman;Dan Geiger;Moises Goldszmidt

  • Using Bayesian networks to analyze expression data

    Nir Friedman;Michal Linial;Iftach Nachman;Dana Pe'er

  • Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data

    Eran Segal;Michael Shapira;Aviv Regev;Aviv Regev;Dana Pe'er

  • Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens

    Atray Dixit;Atray Dixit;Oren Parnas;Biyu Li;Jenny Chen;Jenny Chen

  • Inferring Cellular Networks Using Probabilistic Graphical Models

    Nir Friedman

  • Paternally Induced Transgenerational Environmental Reprogramming of Metabolic Gene Expression in Mammals

    Benjamin R. Carone;Lucas Fauquier;Naomi Habib;Jeremy M. Shea

  • Image segmentation in video sequences: a probabilistic approach

    Nir Friedman;Stuart Russell

  • Tissue classification with gene expression profiles.

    Amir Ben-Dor;Laurakay Bruhn;Nir Friedman;Iftach Nachman

  • Learning Probabilistic Relational Models

    Nir Friedman;Lise Getoor;Daphne Koller;Avi Pfeffer

  • Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks

    Nir Friedman;Daphne Koller

  • Densely Interconnected Transcriptional Circuits Control Cell States in Human Hematopoiesis

    Noa Novershtern;Noa Novershtern;Noa Novershtern;Aravind Subramanian;Lee N. Lawton;Raymond H. Mak

  • Comprehensive comparative analysis of strand-specific RNA sequencing methods

    Joshua Z Levin;Moran Yassour;Moran Yassour;Xian Adiconis;Chad Nusbaum

  • A module map showing conditional activity of expression modules in cancer.

    Eran Segal;Eran Segal;Nir Friedman;Daphne Koller;Aviv Regev

  • Mapping Nucleosome Resolution Chromosome Folding in Yeast by Micro-C

    Tsung-Han S. Hsieh;Assaf Weiner;Bryan R. Lajoie;Job Dekker

  • Context-specific independence in Bayesian networks

    Craig Boutilier;Nir Friedman;Moises Goldszmidt;Daphne Koller

  • Learning bayesian network structure from massive datasets: the «sparse candidate« algorithm

    Nir Friedman;Iftach Nachman;Dana Peér

  • Inferring subnetworks from perturbed expression profiles.

    Dana Pe’er;Aviv Regev;Gal Elidan;Nir Friedman

  • Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning

    Daphne Koller;Nir Friedman

  • A Bayesian Approach to Structure Discovery in Bayesian Networks

    Nir Friedman;Daphne Koller

Frequent Co-Authors

Aviv Regev
Aviv Regev Genentech
Daphne Koller
Daphne Koller insitro Inc.
Joseph Y. Halpern
Joseph Y. Halpern Cornell University
Oliver J. Rando
Oliver J. Rando University of Massachusetts Chan Medical School
Moises Goldszmidt
Moises Goldszmidt Apple (United States)
Nir Hacohen
Nir Hacohen Harvard University
Ido Amit
Ido Amit Weizmann Institute of Science
Joshua Z. Levin
Joshua Z. Levin Broad Institute
Hanah Margalit
Hanah Margalit Hebrew University of Jerusalem
Eran Segal
Eran Segal Weizmann Institute of Science

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