Evidence map›Paper›PMID 39143982›Full record

ArticleBioinformatics advances2024

Current and future directions in network biology.

Marinka Zitnik, Michelle M Li, Aydin Wells, Kimberly Glass, Deisy Morselli Gysi, Arjun Krishnan, T M Murali, Predrag Radivojac, Sushmita Roy, Anaïs Baudot and 27 more

Abstract readEditorial
In one paragraph

Article in Bioinformatics advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed.

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4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

37 authors.

Marinka ZitnikDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.ORCID https://orcid.org/0000-0001-8530-7228
Michelle M LiDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.ORCID https://orcid.org/0000-0003-0223-7485
Aydin WellsDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, United States.ORCID https://orcid.org/0009-0003-1674-4856
Kimberly GlassChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States.ORCID https://orcid.org/0000-0003-4394-5779
Deisy Morselli GysiChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States.
Arjun KrishnanDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, United States.ORCID https://orcid.org/0000-0002-7980-4110
T M MuraliDepartment of Computer Science, Virginia Tech, Blacksburg, VA 24061, United States.ORCID https://orcid.org/0000-0003-3688-4672
Predrag RadivojacKhoury College of Computer Sciences, Northeastern University, Boston, MA 02115, United States.ORCID https://orcid.org/0000-0002-6769-0793
Sushmita RoyDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, United States.
Anaïs BaudotAix Marseille Université, INSERM, MMG, Marseille, France.ORCID https://orcid.org/0000-0003-0885-7933
Serdar BozdagDepartment of Computer Science and Engineering, University of North Texas, Denton, TX 76203, United States.ORCID https://orcid.org/0000-0002-4813-4310
Danny Z ChenDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, United States.ORCID https://orcid.org/0000-0001-6565-2884
Lenore CowenDepartment of Computer Science, Tufts University, Medford, MA 02155, United States.ORCID https://orcid.org/0000-0001-6698-6413
Kapil DevkotaDepartment of Computer Science, Tufts University, Medford, MA 02155, United States.ORCID https://orcid.org/0000-0002-6093-6260
Anthony GitterDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, United States.ORCID https://orcid.org/0000-0002-5324-9833
Sara J C GoslineBiological Sciences Division, Pacific Northwest National Laboratory, Seattle, WA 98109, United States.ORCID https://orcid.org/0000-0002-6534-4774
Pengfei GuDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, United States.
Pietro H GuzziDepartment of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Catanzaro, 88100, Italy.ORCID https://orcid.org/0000-0001-5542-2997
Heng HuangDepartment of Computer Science, University of Maryland College Park, College Park, MD 20742, United States.
Meng JiangDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, United States.
Ziynet Nesibe KesimogluDepartment of Computer Science and Engineering, University of North Texas, Denton, TX 76203, United States.ORCID https://orcid.org/0000-0001-8592-4365
Mehmet KoyuturkDepartment of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH 44106, United States.
Jian MaRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, United States.
Alexander R PicoInstitute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158, United States.
Nataša PržuljDepartment of Computer Science, University College London, London, WC1E 6BT, England.ORCID https://orcid.org/0000-0002-1290-853X
Teresa M PrzytyckaNational Center of Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20814, United States.ORCID https://orcid.org/0000-0002-6261-277X
Benjamin J RaphaelDepartment of Computer Science, Princeton University, Princeton, NJ 08544, United States.ORCID https://orcid.org/0000-0003-1274-048X
Anna RitzDepartment of Biology, Reed College, Portland, OR 97202, United States.ORCID https://orcid.org/0000-0002-7925-5369
Roded SharanSchool of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel.ORCID https://orcid.org/0000-0001-8363-4882
Yang ShenDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, United States.ORCID https://orcid.org/0000-0002-1703-7796
Mona SinghDepartment of Computer Science, Princeton University, Princeton, NJ 08544, United States.
Donna K SlonimDepartment of Computer Science, Tufts University, Medford, MA 02155, United States.ORCID https://orcid.org/0000-0003-3357-437X
Hanghang TongDepartment of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States.
Xinan Holly YangDepartment of Pediatrics, University of Chicago, Chicago, IL 60637, United States.ORCID https://orcid.org/0000-0001-8061-8692
Byung-Jun YoonDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, United States.ORCID https://orcid.org/0000-0001-9328-1101
Haiyuan YuDepartment of Computational Biology, Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, United States.
Tijana MilenkovićDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, United States.

Funding

Combinatorial and graph theoretical approach to systems biology and mol. evo.ZIALM200887 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PRZYTYCKA, TERESA · 2009 to 2025
$24.4M
Resolving and understanding the genomic basis of heterogeneous complex traits and diseasesR35GM128765 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI KRISHNAN, ARJUN · 2018 to 2022
$2.0M
NIGMS NIH HHS R35 GM128765
6 · The paper itself

Abstract

Summary: Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales. Although the field has been around for two decades, it remains nascent. It has witnessed rapid evolution, accompanied by emerging challenges. These stem from various factors, notably the growing complexity and volume of data together with the increased diversity of data types describing different tiers of biological organization. We discuss prevailing research directions in network biology, focusing on molecular/cellular networks but also on other biological network types such as biomedical knowledge graphs, patient similarity networks, brain networks, and social/contact networks relevant to disease spread. In more detail, we highlight areas of inference and comparison of biological networks, multimodal data integration and heterogeneous networks, higher-order network analysis, machine learning on networks, and network-based personalized medicine. Following the overview of recent breakthroughs across these five areas, we offer a perspective on future directions of network biology. Additionally, we discuss scientific communities, educational initiatives, and the importance of fostering diversity within the field. This article establishes a roadmap for an immediate and long-term vision for network biology. Availability and implementation: Not applicable.

Identifiers

PMID39143982
PMCPMC11321866

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.