Jesper Tegnér

About Jesper Tegnér

Jesper Tegnér, With an exceptional h-index of 59 and a recent h-index of 42 (since 2020), a distinguished researcher at King Abdullah University of Science and Technology, specializes in the field of machine learning, genomics, neuroscience, computational biology, Artificial Intelligence.

His recent articles reflect a diverse array of research interests and contributions to the field:

Assembly Theory is a weak version of algorithmic complexity based on LZ compression that does not explain or quantify selection or evolution

Derivation of two iPSC lines (KAIMRCi004-A, KAIMRCi004-B) from a Saudi patient with Biotin-Thiamine-Responsive Basal Ganglia disease (BTBGD) carrying homozygous pathogenic …

Transcriptional Characterization of the Stromal and Endothelial Bone Marrow Microenvironment during Progression from MGUS to Multiple Myeloma

Combined Single-Cell and Spatial Transcriptomics Unveil the Complex Organization of the Non-Immune Human Bone Marrow Microenvironment during Aging

Translating single-cell genomics into cell types

Joint Learning of Node Semantics and Graph Topology using a Transformer in the sparse network regime

IHCV: Discovery of Hidden Time-Dependent Control Variables in Non-Linear Dynamical Systems

LIBRA: an adaptative integrative tool for paired single‐cell multi‐omics data

Jesper Tegnér Information

University

Position

Professor. Bio CS BioE STAT programs Strategic Professor Karolinska

Citations(all)

19636

Citations(since 2020)

7427

Cited By

15491

hIndex(all)

59

hIndex(since 2020)

42

i10Index(all)

159

i10Index(since 2020)

112

Email

University Profile Page

King Abdullah University of Science and Technology

Google Scholar

View Google Scholar Profile

Jesper Tegnér Skills & Research Interests

machine learning

genomics

neuroscience

computational biology

Artificial Intelligence

Top articles of Jesper Tegnér

Title

Journal

Author(s)

Publication Date

Assembly Theory is a weak version of algorithmic complexity based on LZ compression that does not explain or quantify selection or evolution

arXiv preprint arXiv:2403.06629

Felipe S Abrahão

Santiago Hernández-Orozco

Narsis A Kiani

Jesper Tegnér

Hector Zenil

2024/3/11

Derivation of two iPSC lines (KAIMRCi004-A, KAIMRCi004-B) from a Saudi patient with Biotin-Thiamine-Responsive Basal Ganglia disease (BTBGD) carrying homozygous pathogenic …

Maryam Alowaysi

Moayad Baadhaim

Mohammad Al-Shehri

Hajar Alzahrani

Amani Badkok

...

2024/3/6

Transcriptional Characterization of the Stromal and Endothelial Bone Marrow Microenvironment during Progression from MGUS to Multiple Myeloma

bioRxiv

Itziar Cenzano

Miguel Cocera

Azari Bantan

Marta Larrayoz

Amaia Vilas

...

2024

Combined Single-Cell and Spatial Transcriptomics Unveil the Complex Organization of the Non-Immune Human Bone Marrow Microenvironment during Aging

Blood

Itziar Cenzano

Miguel Cocera

Robert Lehmann

Jin Ye

Amaia Vilas-Zornoza

...

2023/12/1

Translating single-cell genomics into cell types

Nature Machine Intelligence

Jesper N Tegner

2023/1

Joint Learning of Node Semantics and Graph Topology using a Transformer in the sparse network regime

bioRxiv

Aidyn Ubingazhibov

David Gomez-Cabrero

Narsis Kiani

Jesper Tegner

2023

IHCV: Discovery of Hidden Time-Dependent Control Variables in Non-Linear Dynamical Systems

arXiv preprint arXiv:2304.02443

Juan Munoz

Subash Balsamy

Juan P Bernal-Tamayo

Ali Balubaid

Alberto Maillo Ruiz de Infante

...

2023/4/5

LIBRA: an adaptative integrative tool for paired single‐cell multi‐omics data

Quantitative Biology

Xabier Martinez‐de‐Morentin

Sumeer A Khan

Robert Lehmann

Sisi Qu

Alberto Maillo

...

2023/9

Reusability report: Learning the transcriptional grammar in single-cell RNA-sequencing data using transformers

Nature Machine Intelligence

Sumeer Ahmad Khan

Alberto Maillo

Vincenzo Lagani

Robert Lehmann

Narsis A Kiani

...

2023/12

Foundation Models Meet Imbalanced Single-Cell Data When Learning Cell Type Annotations

bioRxiv

Abdel Rahman Alsabbagh

Albert Maillo Ruiz de Infante

David Gomez-Cabrero

Narsis Kiani

Sumeer Ahmad Khan

...

2023

LEP-AD: Language Embedding of Proteins and Attention to Drugs predicts drug target interactions

bioRxiv

Anuj Daga

Sumeer Ahmad Khan

David Gomez Cabrero

Robert Hoehndorf

Narsis A Kiani

...

2023/3/15

Generation of myoglobin (MB)-knockout human embryonic stem cell (hESC) line (KAIMRCe002-A-1S) using CRISPR/Cas9 technology

Stem Cell Research

Maryam Alowaysi

Mohammad Al-Shehri

Moayad Baadhaim

Hajar AlZahrani

Doaa Aboalola

...

2023/9/1

Comprehensive Characterization of the Bone Marrow Microenvironment Transcriptional Remodeling in the Progression from MGUS to Smoldering and Multiple Myeloma

Blood

Itziar Cenzano

Miguel Cocera

Azari Bantan

Marta Larrayoz

Amaia Vilas-Zornoza

...

2023/11/28

Representational Learning from Healthy Multi-Tissue Human RNA-seq Data such that Latent Space Arithmetics Extracts Disease Modules

bioRxiv

Hendrik Arnold de Weerd

Dimitri Guala

Mika Gustafsson

Jane Synnergren

Jesper Tegner

...

2023

adaga06/LEP-AD: Repurposing ESM pretrained models for DTI

Anuj Daga

Sumeer Ahmad Khan

David Gomez-Cabrero

Robert Hoehndorf

Narsis A Kiani

...

2023/2/9

DNA methylation signatures of multiple sclerosis occur independently of known genetic risk and are primarily attributed to B cells and monocytes

International Journal of Molecular Sciences

Alexandre Xavier

Vicki E Maltby

Ewoud Ewing

Maria Pia Campagna

Sean M Burnard

...

2023/8/8

Spatial Transcriptomics Unveils Novel Potential Mechanisms of Disease in a MI cγ1 Multiple Myeloma in vivo Model

Blood

Laura Sudupe

Emma Muiños-Lopez

Isabel A Calvo

Ana Rosa Lopez-Perez

Amaia Vilas-Zornoza

...

2023/11/28

HLA-based banking of human induced pluripotent stem cells in Saudi Arabia

bioRxiv

Maryam Alowaysi

Robert Lehmann

Mohammad Al-Shehri

Moayad Baadheim

Hajar Alzahrani

...

2023

scAEGAN: Unification of single-cell genomics data by adversarial learning of latent space correspondences

Plos one

Sumeer Ahmad Khan

Robert Lehmann

Xabier Martinez-de-Morentin

Alberto Maillo

Vincenzo Lagani

...

2023/2/3

The future of fundamental science led by generative closed-loop artificial intelligence

arXiv preprint arXiv:2307.07522

Hector Zenil

Jesper Tegnér

Felipe S Abrahão

Alexander Lavin

Vipin Kumar

...

2023/7/9

See List of Professors in Jesper Tegnér University(King Abdullah University of Science and Technology)

Co-Authors

H-index: 113
Sten Grillner

Sten Grillner

Karolinska Institutet

H-index: 81
Fredrik Piehl

Fredrik Piehl

Karolinska Institutet

H-index: 58
Torkel Klingberg

Torkel Klingberg

Karolinska Institutet

H-index: 47
Anders Lansner

Anders Lansner

Kungliga Tekniska högskolan

H-index: 45
Ioannis Tsamardinos

Ioannis Tsamardinos

University of Crete

H-index: 44
Jagodic Maja

Jagodic Maja

Karolinska Institutet

academic-engine