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Biology and Biochemistry

D-Index
82
Citations
77930
World Ranking
3597
National Ranking
37

Overview

Anders Krogh is affiliated with the University of Copenhagen in Denmark and has contributed extensively to the fields of Biochemistry, Genetics and Molecular Biology. Their research covers a range of specialized areas including Molecular Biology, Cancer Research, Genetics, Artificial Intelligence, and Computer Vision and Pattern Recognition.

The scientist's published work addresses various key topics, such as:

  • Single-cell and spatial transcriptomics
  • RNA and protein synthesis mechanisms
  • Gene expression and cancer classification
  • Cancer Genomics and Diagnostics
  • Genomics and Phylogenetic Studies
  • Machine Learning in Bioinformatics
  • Genomics and Rare Diseases

Among their recent scientific contributions are the following papers:

  • DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks, 2022, bioRxiv (Cold Spring Harbor Laboratory)
  • Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology, 2023, JCO Clinical Cancer Informatics
  • Secreted breast tumor interstitial fluid microRNAs and their target genes are associated with triple-negative breast cancer, tumor grade, and immune infiltration, 2020, Breast Cancer Research
  • High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers, 2020, Molecular Oncology
  • Taxonomic classification method for metagenomics based on core protein families with Core-Kaiju, 2020, Nucleic Acids Research

Frequent co-authors collaborating with Anders Krogh include:

  • Viktoria Schuster
  • Yuhu Liang
  • Iñigo Prada-Luengo
  • Thilde Terkelsen
  • Piero Fariselli

Anders Krogh's publications have appeared most often in the following venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Blood
  • arXiv (Cornell University)
  • BMC Genomics

The breadth of Krogh's work integrates computational and experimental approaches. Their research encompasses machine learning applications within bioinformatics and medical genetics, particularly in cancer genomics and diagnostics. This interdisciplinary approach supports studies in gene expression mechanisms alongside emerging technologies such as synthetic data generation and high-throughput proteomics.

Best Publications

  • Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes

    A Krogh;B Larsson;G von Heijne;E L Sonnhammer

  • Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence

    S. T. Cole;R. Brosch;J. Parkhill;T. Garnier

  • Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids

    Richard Durbin;Sean Eddy;Anders Stærmose Krogh;Graeme Mitchison

  • A Hidden Markov Model for Predicting Transmembrane Helices in Protein Sequences

    Erik L. L. Sonnhammer;Gunnar von Heijne;Anders Krogh

  • HIDDEN MARKOV MODELS IN COMPUTATIONAL BIOLOGY: APPLICATIONS TO PROTEIN MODELING

    Anders Krogh;Michael Brown;I. S Mian;Kimmen Sjolander

  • A combined transmembrane topology and signal peptide prediction method.

    Lukas Käll;Anders Krogh;Erik L.L Sonnhammer

  • A Simple Weight Decay Can Improve Generalization

    Anders Krogh;John A. Hertz

  • Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server.

    Lukas Käll;Anders Krogh;Erik L.L. Sonnhammer

  • Fast and sensitive taxonomic classification for metagenomics with Kaiju

    Peter Menzel;Kim Lee Ng;Anders Krogh

  • Complete genome sequence of a multiple drug resistant Salmonella enterica serovar Typhi CT18

    J. Parkhill;G. Dougan;K. D. James;N. R. Thomson

  • Programmed Cell Death 4 (PDCD4) Is an Important Functional Target of the MicroRNA miR-21 in Breast Cancer Cells

    Lisa B. Frankel;Nanna R. Christoffersen;Anders Jacobsen;Morten Lindow

  • Prediction of lipoprotein signal peptides in Gram-negative bacteria

    Agnieszka S. Juncker;Hanni Willenbrock;Gunnar von Heijne;Søren Brunak

  • Ancient human genome sequence of an extinct Palaeo-Eskimo

    Morten Rasmussen;Yingrui Li;Stinus Lindgreen;Jakob Skou Pedersen

  • Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse.

    Ludovic Orlando;Aurelien Ginolhac;Guojie Zhang;Duane Froese

  • An Aboriginal Australian Genome Reveals Separate Human Dispersals into Asia

    Morten Rasmussen;Xiaosen Guo;Yong Wang;Kirk E. Lohmueller

  • Whole-genome sequencing of cultivated and wild peppers provides insights into Capsicum domestication and specialization

    Cheng Qin;Cheng Qin;Changshui Yu;Yaou Shen;Xiaodong Fang;Xiaodong Fang

  • JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update

    Jan Christian Bryne;Eivind Valen;Man-Hung Eric Tang;Troels Torben Marstrand

  • What are artificial neural networks

    Anders Krogh

  • Prediction of Signal Peptides and Signal Anchors by a Hidden Markov Model

    Henrik Nielsen;Anders Krogh

  • Hidden Markov models for sequence analysis: extension and analysis of the basic method

    Richard Hughey;Anders Stærmose Krogh

Frequent Co-Authors

Søren Brunak
Søren Brunak University of Copenhagen
Sean R. Eddy
Sean R. Eddy Harvard University
Ole Winther
Ole Winther Technical University of Denmark
Anders H. Lund
Anders H. Lund University of Copenhagen
Eske Willerslev
Eske Willerslev University of Copenhagen
Rasmus Nielsen
Rasmus Nielsen University of California, Berkeley
Vadim N. Gladyshev
Vadim N. Gladyshev Brigham and Women's Hospital
Xiaodong Fang
Xiaodong Fang Beijing Genomics Institute
Ludovic Orlando
Ludovic Orlando Paul Sabatier University
Xun Xu
Xun Xu Beijing Genomics Institute

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