Erik van Nimwegen | |
|---|---|
 Erik van Nimwegen (2015) | |
| Born | 5 November 1970 |
| Nationality | Dutch |
| Scientific career | |
| Fields | Computational Biology |
| Institutions | University of Amsterdam, Santa Fe Institute, Utrecht University, Rockefeller University, Swiss Institute of Bioinformatics, Biozentrum University of Basel |
Erik van Nimwegen (born 5 November 1970 in Amsterdam, Netherlands) is a Dutch computational biologist and Professor at the Biozentrum of the University of Basel, Switzerland. [1]
Erik van Nimwegen studied theoretical physics at the University of Amsterdam. He performed his PhD studies at the Santa Fe Institute (SFI) in Santa Fe New Mexico, receiving his PhD from the Faculty of Biology at Utrecht University in 1999. This was followed by a year of post-doc studies at the SFI, and three years as a fellow at the Center of Studies in Physics and Biology at the Rockefeller University, New York. Since 2003 he is Professor of Computational Biology at the Biozentrum of the University of Basel, [2] and group leader at the Swiss Institute of Bioinformatics since 2004. [3]
Erik van Nimwegen’s main research topics concern genome evolution and the function and evolution of the regulatory networks by which cells control gene expression. [4] [5] He develops mathematical models for analyzing how regulatory networks evolve and function, and computational methods for the reconstruction of such networks from large biological data-sets. Van Nimwegen's work includes a general model for the evolution of robustness against mutations and the identification of a number of universal scaling laws of genome evolution. [6] Further research topics are the development of general Bayesian methods for transcription factor and miRNA binding site prediction as well as models for inferring regulatory networks from genome-wide expression and chromatin state data. [7]
Since 2010 Member of the editorial board of the journal PLoS Computational Biology . [8]
Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.
In genetics, the phenotype is the set of observable characteristics or traits of an organism. The term covers the organism's morphology, its developmental processes, its biochemical and physiological properties, its behavior, and the products of behavior. An organism's phenotype results from two basic factors: the expression of an organism's genetic code and the influence of environmental factors. Both factors may interact, further affecting the phenotype. When two or more clearly different phenotypes exist in the same population of a species, the species is called polymorphic. A well-documented example of polymorphism is Labrador Retriever coloring; while the coat color depends on many genes, it is clearly seen in the environment as yellow, black, and brown. Richard Dawkins in 1978 and then again in his 1982 book The Extended Phenotype suggested that one can regard bird nests and other built structures such as caddisfly larva cases and beaver dams as "extended phenotypes".
A transposable element is a nucleic acid sequence in DNA that can change its position within a genome, sometimes creating or reversing mutations and altering the cell's genetic identity and genome size. Transposition often results in duplication of the same genetic material. In the human genome, L1 and Alu elements are two examples. Barbara McClintock's discovery of them earned her a Nobel Prize in 1983. Its importance in personalized medicine is becoming increasingly relevant, as well as gaining more attention in data analytics given the difficulty of analysis in very high dimensional spaces.
Molecular evolution describes how inherited DNA and/or RNA change over evolutionary time, and the consequences of this for proteins and other components of cells and organisms. Molecular evolution is the basis of phylogenetic approaches to describing the tree of life. Molecular evolution overlaps with population genetics, especially on shorter timescales. Topics in molecular evolution include the origins of new genes, the genetic nature of complex traits, the genetic basis of adaptation and speciation, the evolution of development, and patterns and processes underlying genomic changes during evolution.
The SIB Swiss Institute of Bioinformatics is an academic not-for-profit foundation which federates bioinformatics activities throughout Switzerland.
Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, including both DNA and RNA sequence as well as other "post-genomic" data. These, in combination with computational and statistical approaches to understanding the function of the genes and statistical association analysis, this field is also often referred to as Computational and Statistical Genetics/genomics. As such, computational genomics may be regarded as a subset of bioinformatics and computational biology, but with a focus on using whole genomes to understand the principles of how the DNA of a species controls its biology at the molecular level and beyond. With the current abundance of massive biological datasets, computational studies have become one of the most important means to biological discovery.
Cis-regulatory elements (CREs) or cis-regulatory modules (CRMs) are regions of non-coding DNA which regulate the transcription of neighboring genes. CREs are vital components of genetic regulatory networks, which in turn control morphogenesis, the development of anatomy, and other aspects of embryonic development, studied in evolutionary developmental biology.
The mir-2 microRNA family includes the microRNA genes mir-2 and mir-13. Mir-2 is widespread in invertebrates, and it is the largest family of microRNAs in the model species Drosophila melanogaster. MicroRNAs from this family are produced from the 3' arm of the precursor hairpin. Leaman et al. showed that the miR-2 family regulates cell survival by translational repression of proapoptotic factors. Based on computational prediction of targets, a role in neural development and maintenance has been suggested.
Trans-regulatory elements (TRE) are DNA sequences encoding upstream regulators, which may modify or regulate the expression of distant genes. Trans-acting factors interact with cis-regulatory elements to regulate gene expression. TRE mediates expression profiles of a large number of genes via trans-acting factors. While TRE mutations affect gene expression, it is also one of the main driving factors for evolutionary divergence in gene expression.
In evolutionary biology, robustness of a biological system is the persistence of a certain characteristic or trait in a system under perturbations or conditions of uncertainty. Robustness in development is known as canalization. According to the kind of perturbation involved, robustness can be classified as mutational, environmental, recombinational, or behavioral robustness etc. Robustness is achieved through the combination of many genetic and molecular mechanisms and can evolve by either direct or indirect selection. Several model systems have been developed to experimentally study robustness and its evolutionary consequences.
John Quackenbush is an American computational biologist and genome scientist. He is a professor of biostatistics and computational biology and a professor of cancer biology at the Dana–Farber Cancer Institute (DFCI), as well as the director of its Center for Cancer Computational Biology (CCCB). Quackenbush also holds an appointment as a professor of computational biology and bioinformatics in the Department of Biostatistics at the Harvard School of Public Health.
James P. Crutchfield is an American mathematician and physicist. He received his B.A. summa cum laude in physics and mathematics from the University of California, Santa Cruz, in 1979 and his Ph.D. in physics there in 1983. He is currently a professor of physics at the University of California, Davis, where he is director of the Complexity Sciences Center—a new research and graduate program in complex systems. Prior to this, he was research professor at the Santa Fe Institute for many years, where he ran the Dynamics of Learning Group and SFI's Network Dynamics Program. From 1985 to 1997, he was a research physicist in the physics department at the University of California, Berkeley. He has been a visiting research professor at the Sloan Center for Theoretical Neurobiology, University of California, San Francisco; a postdoctoral fellow of the Miller Institute for Basic Research in Science at UCB; a UCB physics department IBM postdoctoral fellow in condensed matter physics; a distinguished visiting research professor of the Beckman Institute at the University of Illinois, Urbana-Champaign; and a Bernard Osher Fellow at the San Francisco Exploratorium.
Research at the Biozentrum of the University of Basel is dedicated to the central question of how molecules and cells create life − from atom to organism, and from the physics of life to the dynamics of multicellular systems. Accordingly, the scientists at the Biozentrum are active in a wide range of research fields. These disciplines are not strictly separated from each other, but often overlap, thus leading to new questions and collaborations.
A neutral network is a set of genes all related by point mutations that have equivalent function or fitness. Each node represents a gene sequence and each line represents the mutation connecting two sequences. Neutral networks can be thought of as high, flat plateaus in a fitness landscape. During neutral evolution, genes can randomly move through neutral networks and traverse regions of sequence space which may have consequences for robustness and evolvability.
Mihaela Zavolan is a system biologist and Professor at the Biozentrum of the University of Basel.
Tumour heterogeneity describes the observation that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation, and metastatic potential. This phenomenon occurs both between tumours and within tumours. A minimal level of intra-tumour heterogeneity is a simple consequence of the imperfection of DNA replication: whenever a cell divides, a few mutations are acquired—leading to a diverse population of cancer cells. The heterogeneity of cancer cells introduces significant challenges in designing effective treatment strategies. However, research into understanding and characterizing heterogeneity can allow for a better understanding of the causes and progression of disease. In turn, this has the potential to guide the creation of more refined treatment strategies that incorporate knowledge of heterogeneity to yield higher efficacy.
Sarah Amalia Teichmann is a German scientist who is head of cellular genetics at the Wellcome Sanger Institute and a visiting research group leader at the European Bioinformatics Institute (EMBL-EBI). She serves as director of research in the Cavendish Laboratory, at the University of Cambridge and a senior research fellow at Churchill College, Cambridge.
Julian John Thurstan Gough was a Group Leader in the Laboratory of Molecular Biology (LMB) of the Medical Research Council (MRC). He was previously a professor of bioinformatics at the University of Bristol.
Barbara J. Wold is the Bren Professor of Molecular Biology, the principal investigator of the Wold Lab at the California Institute of Technology (Caltech) and the principal investigator of the Functional Genomics Resource Center at the Beckman Institute at Caltech. Wold was director of the Beckman Institute at Caltech from 2001 to 2011.
Katherine Snowden Pollard is the Director of the Gladstone Institute of Data Science and Biotechnology and a professor at the University of California, San Francisco (UCSF). She is a Chan Zuckerberg Biohub Investigator. She was awarded Fellowship of the International Society for Computational Biology in 2020 and the American Institute for Medical and Biological Engineering in 2021 for outstanding contributions to computational biology and bioinformatics.
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