Peer Bork
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Peer Bork

Molecular Systems Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

Research Focus & Metrics

Academic Career Length

38Years (1989-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2001 in Nature
Verified
Journal Article
Open access
PDF file
ELEric S. Lander
Eric S. Lander
LLLauren M. Linton
Lauren M. Linton
BBBruce Birren
Bruce Birren
CNChad Nusbaum
Chad Nusbaum
MZMichael C. Zody
Michael C. Zody
MMMichael J. Morgan
Michael J. Morgan
The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

22 November 2018 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
DSDamian Szklarczyk
Damian Szklarczyk
AGAnnika L Gable
Annika L Gable
DLDavid Lyon
David Lyon
AJAlexander Junge
Alexander Junge
SWStefan Wyder
Stefan Wyder
CMChristian von Mering
Christian von Mering
Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

12 November 2022 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
DSDamian Szklarczyk
Damian Szklarczyk
RKRebecca Kirsch
Rebecca Kirsch
MKMikaela Koutrouli
Mikaela Koutrouli
KNKaterina Nastou
Katerina Nastou
FMFarrokh Mehryary
Farrokh Mehryary
CMChristian von Mering
Christian von Mering
Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database (https://string-db.org/) systematically collects and integrates protein–protein interactions—both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes.

4 March 2010 in Nature
Verified
Journal Article
Open access
PDF file
MCMetaHIT Consortium
MetaHIT Consortium
JQJunjie Qin
Junjie Qin
RLRuiqiang Li
Ruiqiang Li
JRJeroen Raes
Jeroen Raes
MAManimozhiyan Arumugam
Manimozhiyan Arumugam
JWJun Wang
Jun Wang
To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, ∼150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively.

28 October 2014 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
DSDamian Szklarczyk
Damian Szklarczyk
AFAndrea Franceschini
Andrea Franceschini
SWStefan Wyder
Stefan Wyder
SFSofia Kirke Forslund
Sofia Kirke Forslund
DHDavide Heller
Davide Heller
CMChristian von Mering
Christian von Mering
The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein–protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein–protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.

20 April 2011 in Nature
Verified
Journal Article
Closed access
PDF file
MMMetaHIT Consortium (additional members)
MetaHIT Consortium (additional members)
MAManimozhiyan Arumugam
Manimozhiyan Arumugam
JRJeroen Raes
Jeroen Raes
EPEric Pelletier
Eric Pelletier
DPDenis Le Paslier
Denis Le Paslier
PBPeer Bork
Peer Bork