World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
59
Citations
18312
World Ranking
12303
National Ranking
118

Overview

Michal Linial is affiliated with the Hebrew University of Jerusalem in Israel. Their research contributions span diverse areas within biochemistry, genetics, molecular biology, and medicine, with a strong focus on molecular biology, cancer research, genetics, infectious diseases, and neurology.

Their recent scholarly output includes publications across multiple venues and topics. Notable recent papers include:

  • ProteinBERT: a universal deep-learning model of protein sequence and function, 2022, Bioinformatics
  • The language of proteins: NLP, machine learning & protein sequences, 2021, Computational and Structural Biotechnology Journal
  • The SARS-CoV-2 Exerts a Distinctive Strategy for Interacting with the ACE2 Human Receptor, 2020, Viruses
  • PWAS: proteome-wide association study-linking genes and phenotypes by functional variation in proteins, 2020, Genome Biology
  • Open problems in human trait genetics, 2022, Genome Biology

Michal Linial's work intersects multiple research themes. The main topics they have addressed include:

  • Genetic associations and epidemiology
  • Cancer-related molecular mechanisms research
  • Bioinformatics and genomic networks
  • Epigenetics and DNA methylation
  • MicroRNA in disease regulation
  • Neuroinflammation and neurodegeneration mechanisms
  • RNA and protein synthesis mechanisms

The scientist frequently coauthors with a number of researchers in their field. Frequent collaborators include:

  • Keren Zohar
  • Nadav Brandes
  • Dan Ofer
  • Tsiona Eliyahu
  • Roei Zucker

Publications by Michal Linial are often featured in venues that support rapid dissemination of findings, including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Preprints.org
  • Research Square
  • International Journal of Molecular Sciences
  • Vaccines

The breadth of their work is reflected in the distribution of publications across main fields of study, predominantly Biochemistry, Genetics and Molecular Biology with 193 publications, followed by Medicine with 74. Subfields emphasize Molecular Biology with 105 papers, Cancer Research at 44, Genetics at 37, Infectious Diseases and Neurology each with 18 publications. The spectrum illustrates a strong interdisciplinary approach combining experimental biology with computational methods.

Best Publications

  • Using Bayesian networks to analyze expression data

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

  • Insights into social insects from the genome of the honeybee Apis mellifera

    George M. Weinstock;Gene E. Robinson;Richard A. Gibbs;Kim C. Worley

  • A large-scale evaluation of computational protein function prediction

    Predrag Radivojac;Wyatt T Clark;Tal Ronnen Oron;Alexandra M Schnoes

  • ProteinBERT: A universal deep-learning model of protein sequence and function

    Dan Ofer;Nadav Brandes;Michal Linial;Nadav Rappoport

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • Vesicular neurotransmitter transporters: from bacteria to humans.

    S Schuldiner;A Shirvan;M Linial

  • Novel Unsupervised Feature Filtering of Biological Data

    Roy Varshavsky;Assaf Gottlieb;Michal Linial;David Horn

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • Protein function annotation by homology-based inference

    Yaniv Loewenstein;Domenico Raimondo;Oliver C Redfern;James Watson

  • Viral adaptation to host: a proteome-based analysis of codon usage and amino acid preferences.

    Iris Bahir;Menachem Fromer;Yosef Prat;Michal Linial

  • The language of proteins: NLP, machine learning & protein sequences.

    Dan Ofer;Nadav Brandes;Michal Linial

  • Brain contains two forms of synaptic vesicle protein 2.

    Sandra M. Bajjalieh;Karen Peterson;Michal Linial;Richard H. Scheller

  • ProtoMap: automatic classification of protein sequences and hierarchy of protein families

    Golan Yona;Nathan Linial;Michal Linial

  • Polysaccharide-oligoamine based conjugates for gene delivery.

    Tony Azzam;Hagit Eliyahu;Libi Shapira;Michal Linial

  • Cellular and molecular biology of the presynaptic nerve terminal.

    W S Trimble;M Linial;R H Scheller

  • Nonlinear optical measurement of membrane potential around single molecules at selected cellular sites.

    Gadi Peleg;Aaron Lewis;Michal Linial;Leslie M. Loew

  • Efficient algorithms for accurate hierarchical clustering of huge datasets

    Yaniv Loewenstein;Elon Portugaly;Menachem Fromer;Michal Linial

  • The SARS-CoV-2 Exerts a Distinctive Strategy for Interacting with the ACE2 Human Receptor.

    Esther S. Brielle;Dina Schneidman-Duhovny;Michal Linial

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Nathan Linial
Nathan Linial Hebrew University of Jerusalem
Burkhard Rost
Burkhard Rost Technical University of Munich
Menachem Fromer
Menachem Fromer Broad Institute
Christophe Dessimoz
Christophe Dessimoz University College London
Daisuke Kihara
Daisuke Kihara Purdue University West Lafayette
David T. Jones
David T. Jones University College London
Tapio Salakoski
Tapio Salakoski University of Turku
Predrag Radivojac
Predrag Radivojac Northeastern University
Thomas Lengauer
Thomas Lengauer Max Planck Institute for Informatics
Pardis C. Sabeti
Pardis C. Sabeti Harvard University

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