My research interests lie mainly in two areas: The first is the study of structural and functional complexity in biology from the perspective of algorithmic information theory, as well as interdisciplinary applications of algorithmic information theory more generally. The second is network analysis, where I am interested in both method development and in interdisciplinary applications of network analysis to biology, the humanities, and social sciences.
Some research areas and recent results are outlined below.
A periodic table of protein
complexes
(Science
2015; Nature Communications 2015)
Biological evolution has produced an enormous variety of protein
complexes, which arise when several proteins bind together to form
larger structures. We show that the vast majority of protein complexes
can be broken down in terms of three different fundamental steps of
protein evolution. These steps can combine in many different ways,
giving rise to the observed variety of protein complexes. What this
reveals is that heteromeric protein complexes, which are complexes
that consist of more than one type of protein, can be represented as
homomeric complexes of repeated multi-protein units. This approach
also allows us to classify protein complexes in a periodic table, and
to predict topologies of complexes that have not been observed yet.
The periodic table of protein complexes can be browsed here.
Related to this we have also explored protein complexes of uneven stoichiometry, which represent exceptions to the periodic table (Nature Communications 2015).
Universal properties of genotype-phenotype
maps
(Biophysical Journal 2023; Royal Society Interface
2023 (2); Royal Society Interface
2023; Nature Ecology & Evolution
2022; PNAS
2022; Europhysics Letters
2022; Royal Society Interface
2022; Royal Society Interface
2021; Royal Society Interface
2020; Royal Society Interface
2020 (2); Europhysics Letters
2018; Royal Society Interface
2018; Royal Society Interface
2017; PLOS Computational Biology
2016; Royal Society Interface
2015; Royal Society Interface 2014)
We introduce a simple genotype-phenotype (GP) map for biological
self-assembly on a lattice, and show that it shares many properties
with the well-established GP maps of both RNA secondary structure and
the HP model. These properties include a heavily skewed distribution
of the number of genotypes per phenotype, shape space covering, and
positively correlated phenotypic evolvability and robustness. The fact
that these important properties emerge in three very different GP maps
underline their fundamental importance for biological evolution. It
also means that the lattice model, which is highly simplified and
therefore tractable, can be used to study a wide variety of
evolutionary phenomena.
In further work (2015) we show that all of the properties described above also arise in a much simpler GP map. The defining characteristic of this simple map is the presence of 'coding' and 'non-coding' sequence regions. The boundary between these two regions is itself defined in the sequence, much like start and stop codons in DNA. The fact that the properties of biologically realistic GP maps emerge in this extremely simple model suggests that the fundamental organisation of biological sequences into constrained and unconstrained regions has a profound impact on the structure of GP maps, and therefore on biological evolution.
We have demonstrated that genotypes of the same phenotype are highly correlated (2016), and re-examined the importance of the mutable boundary between constrained and unconstrained sequences (2018), showing that it leads to a positive correlation of phenotypic evolvability and robustness.
We have also explored ways to measure structural properties of the RNA secondary structure GP map using small samples of genotypes, and investigated the topology of neutral components in genotype space (2020). In addition we have examined the genotype-phenotype map of RNA secondary structure with regard to insertions and deletions (2021), and developed a fast approach for neutral set size estimation based on free energy (2022).
In 2022 we published results in PNAS in collaboration with the research group of Ard Louis, demonstrating a close relationship between neutral spaces and phenotypic complexity, which offers an explanation for the ubiquity of symmetry and modularity in biological evolution.
Also in 2022 (published in Nature Ecology & Evolution) we showed that fitness landscapes are in general likely to be highly navigable due to structural properties of genotype-phenotype maps, meaning that these landscape contain very few valleys.
In the context of biological complexity and GP maps I co-organised the ESFCB 2012 conference on the evolution of structural and functional complexity in biology, and the IWGPM 2016 workshop on genotype-phenotype maps.
Self-assembly, modularity and physical
complexity
(PLOS Computational Biology
2019; Physical Review E
2016; Physical Review E 2016
(2); Physical Review E
2011; Physical Review E 2010; see
also Royal Society Interface 2014)
Self-assembly is not just a ubiquitous phenomenon in biology and
physics, it is also a language that can be used to describe a physical
structure, and measure its complexity and modularity. To illustrate
this, we introduce a versatile lattice model of self-assembly, before
applying our approach to more general structures such as molecules and
protein complexes. In further work we show that genetic algorithms can
be used in conjunction with our lattice model to answer questions
about the emergence of symmetry and modularity in biological
evolution.
In our most recent contributions on this topic we also study non-deterministic self-assembly in this lattice model. We show that even very simple non-deterministic two-tile sets can exhibit a wide variety of concentration-dependent growth behaviours. Furthermore we also demonstrate, both computationally and experimentally, that asymmetric interactions can limit the growth of such non-deterministic tile sets.
Network analysis of historical correspondence
(Huntington Library Quarterly 2023; Huntington Library Quarterly 2023 (2); Oxford University Press 2023; Oxford University Press 2023 (2); Cultural Analytics 2021; Cambridge University Press 2020; History Workshop Journal
2019; English Literary History
2015; Leonardo 2014)
I collaborate with Ruth Ahnert on the AHRC-funded Tudor
Networks of Power project, which examines the correspondence
network of the Tudor State Papers (1509-1603) with around 132,000
letters between around 20,000 individuals across Britain and
Europe. In recent work we show that network analysis of this
correspondence can highlight conspirators and intelligencers, as they
show unique network connectivity profiles due to their particular
historical roles. Together with designer Kim Albrecht
we developed an interactive visualisation of this data, which can be found at tudornetworks.net.
This work is described in our book Tudor Networks of Power (Oxford University Press, 2023), which won the 2024 Richard Deswarte Prize in Digital History, awarded by the Institute of Historical Research, University of London. It was also shortlisted for the 2024 SHARP Book History Prize.
In addition I was a Co-Investigator on the AHRC-funded Networking Archives project (2018-2021), which aimed to (a) combine three archives of Early Modern political and intellectual correspondence into one large network of around 432,000 letters, spanning the sixteenth, seventeenth, and eighteenth centuries across Europe, and (b) use computational analysis to inform, shape, and answer historical research questions, with a particular focus on the history of intelligence networks. This project was the subject of a special issue of the Huntington Library Quarterly.
In previous work we applied network analysis to a curated social network of the Protestant underground community during the reign of Mary I of England (1553-1558), derived from the contents of several hundred letters sent by members of this community. This quantitative approach identifies individuals in the network who did not necessarily have many connections to others, but who nevertheless occupied strategically important positions in the network. The importance of these individuals is confirmed by historical evidence of their role as sustainers who passed messages, provided shelter and financial support, and who continued to hold the network together after most of the leading figures had been executed by Mary I. This work was published in English Literary History (2015).
This work was also covered in the New Scientist.
With Ruth Ahnert, Nicole Coleman, and Scott Weingart I have written a related book, The Network Turn (Cambridge University Press, published Open Access), which examines the use of network analysis in the Arts and Humanities.
Network analysis of chemical flavour
compounds
(Flavour
2013; Scientific Reports 2011)
Using network analysis we investigate the widespread hypothesis that
foods with compatible flavours share chemical flavour compounds. Until
now this hypothesis has relied on anecdotal rather than quantitative
evidence. We construct a bipartite network of flavour compounds and
ingredients, and compare it to large recipe data sets. This reveals
that the shared compound hypothesis holds in some regional cuisines
but not in others. More generally our analysis demonstrates how the
type of large-scale data analysis that has transformed biology in
recent years can lead to new results in other fields, such as food
science.
Our article in Scientific Reports was the most downloaded article across all Nature Publishing Group journals in December 2011, exceeding 100,000 PDF downloads and HTML page views in the first four weeks following publication. It also received attention from the Scientific American, Nature News, New Scientist, The Huffington Post, The Technology Review, BioTechniques, and Ingeniøren, among others. A poster of the network between food ingredients can be downloaded here.
In the context of this work I also organised a Royal Society International Scientific Seminar in 2014, bringing together a wide range of experts including computational scientists, food scientists, neuroscientists, and chefs to discuss the impact of data science on food consumption and culinary culture.
Power graph compression of networks reveals dominant
relationships
(Scientific Reports
2014; Molecular BioSystems 2013; see
also Nature 2015)
We show that compression of complex networks into power graphs with
freely overlapping power nodes allows us to detect dominant
connectivity patterns in a wide range of different networks. This
approach can be applied to undirected, directed and bipartite networks
such as social networks, food webs and recipe-ingredient
networks. When applied to genetic transcription networks we can assign
meaning to power nodes by using GO term enrichment, which reveals that
functional modules in genetic transcription networks are highly
overlapping.
This method has also been used to map the functional organisation of the gene regulatory network in Arabidopsis responsible for xylem specification and secondary wall biosynthesis (Nature 2015).
Pattern detection in microarray
data
(Science
2010; PLOS One
2008; Bioinformatics 2006)
Over the last decade, microarrays have generated an unprecedented
amount of genetic expression data. Here we introduce an approach for
detecting statistically significant patterns in these datasets without
making prior assumptions about the nature of the pattern. This method
is based on concepts from Algorithmic Information Theory.
I am also interested in genome statistics, Boolean
networks, natural language processing, and Gaussian
processes, among other things, and am co-organiser of
the Cambridge Networks
Network meetings. Past research interests of mine include quantum
measurement and molecular dynamics.
E. C. Marin, B. J. Morris, T. Stürner, A. S. Champion, D. Krzeminski, G. Badalamente, M. Gkantia, C. R. Dunne, K. Eichler, S. Takemura, I. F. M. Tamimi, S. Fang, S. S. Moon, H. S. J. Cheong, F. Li, P. Schlegel, S. E. Ahnert, S. Berg, Janelia FlyEM Project Team, G. M. Card, M. Costa, D. Shepherd, G. S. X. E. Jefferis
Systematic annotation of a complete adult male Drosophila nerve cord connectome reveals principles of functional organisation
eLife 13:RP97766 (2024)
H. Hotson, S. E. Ahnert, M. Lewis
Searching for Missing Links in the Republic of Letters: Vossius and the Dutch Dimension of Hartlib's Circle.
Huntington Library Quarterly 86 (2) 283-313 (2023)
R. Midura, S. E. Ahnert, R. Ahnert
Shadow Networks: Identifying Intercepted Letters in the Elizabethan State Papers Foreign
Huntington Library Quarterly 86 (2) 345-375 (2023)
R. Ahnert, S. E. Ahnert
Chapter 10: Networks
in Archives: Power, Truth, and Fiction, A. Prescott and A. Wiggins (Eds.), Oxford University Press (2023)
N. S. Martin, S. E. Ahnert
The Boltzmann distributions of molecular structures predict likely changes through random mutations
Biophysical Journal 122 (22), 4467 (2023)
R. Ahnert, S. E. Ahnert
Tudor Networks of Power
Oxford University Press (2023)
P. Garcia Galindo, S. E. Ahnert, N. S. Martin
The non-deterministic genotype-phenotype map of RNA secondary structure
Journal of the Royal Society Interface 20, 20230132 (2023)
V. Mohanty, S. F. Greenbury, T. Sarkany, S. Narayanan, K. Dingle, S. E. Ahnert, A. A. Louis
Maximum mutational robustness in genotype-phenotype maps follows a self-similar blancmange-like curve
Journal of the Royal Society Interface 20, 20230169 (2023)
E. Corcoran, M. Afshar, S. Curceac, A. Lashkari, M. M. Raza, S. Ahnert, A. Mead, R. Morris
Current data and modeling bottlenecks for predicting crop yields in the United Kingdom
Frontiers in Sustainable Food Systems 7, 1023169 (2023)
A. Karjus, M. C. Solà, T. Ohm, S. E. Ahnert, M. Schich
Compression ensembles quantify aesthetic complexity and the evolution of visual art
EPJ Data Science 12, 21 (2023)
E. Corcoran, L. Siles, S. Kurup, S. E. Ahnert
Automated extraction of pod phenotype data from micro-computed tomography
Frontiers in Plant Science 14:1120182 (2023)
K. Dingle, J. K. Novev, S. E. Ahnert, A. A. Louis
Predicting phenotype transition probabilities via conditional algorithmic probability approximations
Journal of the Royal Society Interface 19, 20220694 (2022)
S. F. Greenbury, A. A. Louis, S. E. Ahnert
The structure of genotype-phenotype maps makes fitness landscapes navigable
Nature Ecology & Evolution 6, 1742 (2022)
N. S. Martin, S. E. Ahnert
Thermodynamics and neutral sets in the RNA sequence-structure map
Europhysics Letters 139, 3 (2022)
N. S. Martin, S. E. Ahnert
Fast free-energy-based neutral set size estimates for the RNA genotype-phenotype map
Journal of the Royal Society Interface 19, 20220072 (2022)
I. G. Johnston, K. Dingle, S. F. Greenbury, C. Q. Camargo, J. P. K. Doye, S. E. Ahnert, A. A. Louis
Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution
Proceedings of the National Academy of Sciences 119, e2113883119 (2022)
P. Roszak, J. O. Heo, B. Blob, K. Toyokura, Y. Sugiyama, M. A. de Luis Balaguer, W. W. Y. Lau, F. Hamey, J. Cirrone, E. Madej, A. M. Bouatta, X. Wang, M. Guichard, R. Ursache, H. Tavares, K. Verstaen, J. Wendrich, C. W. Melnyk, Y. Oda, D. Shasha, S. E. Ahnert, Y. Saeys, B. De Rybel, R. Heidstra, B. Scheres, G. Grossmann, A. P. Mähönen, P. Denninger, B. Göttgens, R. Sozzani, K. D. Birnbaum, Y. Helariutta
Cell-by-cell dissection of phloem development links a maturation gradient to cell specialization.
Science 374, 6575 (2021)
N. S. Martin, S. E. Ahnert
Insertions and deletions in the RNA sequence-structure map
Journal of the Royal Society Interface 18, 20210380 (2021)
S. Manrubia, J. A. Cuesta, J. Aguirre, S. E. Ahnert, L. Altenberg, A. V. Cano, P. Catalán, R. Diaz-Uriarte, S. F. Elena, J. A. García-Martín, P. Hogeweg, B. S. Khatri, J. Krug, A. A. Louis, N. S. Martin, J. L. Payne, M. J. Tarnowski, M. Weiß
From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics
Physics of Life Reviews 38, 55 (2021)
Y. C. Ryan, S. E. Ahnert
The Measure of the Archive: The Robustness of Network Analysis in Early Modern Correspondence
Cultural Analytics 7, 57 (2021)
V. Jouffrey, A. S. Leonard, S. E. Ahnert
Gene duplication and subsequent diversification strongly affect phenotypic evolvability and robustness
Royal Society Open Science 8: 201636 (2021)
Y. Ryan, S. Ahnert, R. Ahnert
Networking Archives: Quantitative History and the Contingent Archive
Proceedings of the Workshop on Computational Humanities Research (CHR 2020), http://ceur-ws.org/Vol-2723/ (2020)
S. Cortijo, M. Bhattarai, J. C. W. Locke, S. E. Ahnert
Co-expression Networks From Gene Expression Variability Between Genetically Identical Seedlings Can Reveal Novel Regulatory Relationships
Frontiers in Plant Science 11, 1876 (2020)
R. Ahnert, S. E. Ahnert, C. N. Coleman, S. B. Weingart
The Network Turn: Changing Perspectives in the Humanities
Cambridge University Press (2020) - published Open Access (download)
M. Weiß, S. E. Ahnert
Neutral components show a hierarchical community structure in the genotype-phenotype map of RNA secondary structure
Journal of the Royal Society Interface 17, 20200608 (2020)
M. Weiß, S. E. Ahnert
Using small samples to estimate neutral component size and robustness in the genotype-phenotype map of RNA secondary structure.
Journal of the Royal Society Interface 17, 20190784 (2020)
K. Schiessl, J. L. S. Lilley, T. Lee, I. Tamvakis, W. Kohlen, P. C. Bailey, A. Thomas, J. Luptak, K. Ramakrishnan, M. D. Carpenter, K. S. Mysore, J. Wen, S. Ahnert, V. A. Grieneisen, G. E. D. Oldroyd
NODULE INCEPTION Recruits the Lateral Root Developmental Program for Symbiotic Nodule Organogenesis in Medicago truncatula
Current Biology 29, 1 (2019)
J. Zhang, G. Eswaran, J. Alonso-Serra, M. Kucukoglu, J. Xiang, W. Yang, A. Elo, K. Nieminen, T. Damén, J.-G. Joung, J.-Y. Yun, J.-H. Lee, L. Ragni, P. Barbier de Reuille, S. E. Ahnert, J.-Y. Lee, A. P. Mähönen, Y. Helariutta
Transcriptional regulatory framework for vascular cambium development in Arabidopsis roots
Nature Plants 5, 1033 (2019)
E. K. Towlson, P. E. Vértes, U. Müller-Sedgwick, S. E. Ahnert
Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls
Frontiers in Psychiatry 10, 611 (2019)
A. S. Leonard, S. E. Ahnert
Evolution of interface binding strengths in simplified model of protein quaternary structure
PLOS Computational Biology 15(6): e1006886 (2019)
S. Cortijo, Z. Aydin, S. E. Ahnert, J. C. W. Locke
Widespread inter-individual gene expression variability in Arabidopsis thaliana
Molecular Systems Biology 15: e8591 (2019)
R. Ahnert, S. E. Ahnert
Metadata, Surveillance and the Tudor State
History Workshop Journal 87, 27 (2019)
V. Sekara, P. Deville, S. E. Ahnert, A.-L. Barabási, R. Sinatra, S. Lehmann
The chaperone effect in scientific publishing
Proceedings of the National Academy of Sciences 115, 12603 (2018)
S. Tesoro, S. E. Ahnert
Non-deterministic genotype-phenotype maps of biological self-assembly
Europhysics Letters 123, 38002 (2018)
W. P. Grant, S. E. Ahnert
Modular decomposition of protein structure using community detection
Journal of Complex Networks, cny014 (2018)
S. Tesoro, S. E. Ahnert, A. S. Leonard
Determinism and boundedness of self-assembling structures
Physical Review E 98, 022113 (2018)
M. Ikeuchi, M. Shibata, B. Rymen, A. Iwase, A.-M. Bågman, L. Watt, D. Coleman, D. S. Favero, T. Takahashi, S. E. Ahnert, S. M. Brady, K. Sugimoto
A Gene Regulatory Network for Cellular Reprogramming in Plant Regeneration
Plant and Cell Physiology, pcy013 (2018)
M. Weiß, S. E. Ahnert
Phenotypes can be robust and evolvable if mutations have non-local effects on sequence constraints
Journal of the Royal Society Interface 15, 20170618 (2018)
S. E. Ahnert, W. P. Grant, C. J. Pickard
Revealing and exploiting hierarchical material structure through complex atomic networks
npj Computational Materials 3, 35 (2017)
G. F. Chami, S. E. Ahnert, N. B. Kabatereine, E. M. Tukahebwa
Social network fragmentation and community health
Proceedings of the National Academy of Sciences 114, E7425 (2017)
S. E. Ahnert
Structural properties of genotype-phenotype maps
Journal of the Royal Society Interface 14, 20170275 (2017)
O. G. Mouritsen, R. Edwards-Stuart, Y.-Y. Ahn, S. E. Ahnert
Data-driven Methods for the Study of Food Perception, Preparation, Consumption, and Culture
Frontiers in ICT 4, 15 (2017)
A. S. Fokas, D. J. Cole, S. E. Ahnert, A. W. Chin
Residue Geometry Networks: A Rigidity-Based Approach to the Amino Acid Network and Evolutionary Rate Analysis
Scientific Reports 6, 33213 (2016)
S. Tesoro, K. Göpfrich, T. Kartanas, U. F. Keyser, S. E. Ahnert
Nondeterministic self-assembly with asymmetric interactions
Physical Review E 94, 022404 (2016)
S. E. Ahnert, T. M. A. Fink
Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties of their dynamical state space
Journal of the Royal Society Interface 13, 20160179 (2016)
S. Tesoro, S. E. Ahnert
Nondeterministic self-assembly of two tile types on a lattice
Physical Review E 93, 042412 (2016) - selected as Editors' Suggestion
S. F. Greenbury, S. Schaper, S. E. Ahnert, A. A. Louis
Genetic correlations greatly increase mutational robustness and can both reduce and enhance evolvability
PLOS Computational Biology 12(3): e1004773 (2016)
S. E. Ahnert, J. A. Marsh, H. Hernandez, C. V. Robinson, S. A. Teichmann
Principles of assembly reveal a periodic table of protein complexes
Science 350, 1331 (2015)
S. F. Greenbury, S. E. Ahnert
The organization of biological sequences into constrained and unconstrained parts determines fundamental properties of genotype-phenotype maps
Journal of The Royal Society Interface 12, 20150724 (2015)
R. Ahnert, S. E. Ahnert
Protestant letter networks in the reign of Mary I: A quantitative approach
English Literary History 82, 1 (2015)
J. Marsh, H. Rees, S. E. Ahnert, S. A. Teichmann
Structural and evolutionary versatility in protein complexes with uneven stoichiometry
Nature Communications 6, 6394 (2015)
M. Taylor-Teeples, L. Lin, M. de Lucas M, G. Turco, T. W. Toal, A. Gaudinier, N. F. Young, G. M. Trabucco, M. T. Veling, R. Lamothe, P. P. Handakumbura, G. Xiong, C. Wang, J. Corwin, N. Tsoukalas, L. Zhang, D. Ware, M. Pauly, D. J. Kliebenstein, K. Dehesh, I. Tagkopoulos, G. Breton, J. Pruneda-Paz, S. E. Ahnert, S. A. Kay, S. P. Hazen, S. M. Brady
An Arabidopsis Gene Regulatory Network for Xylem Specification and Secondary Wall Biosynthesis
Nature 517, 571 (2015)
S. Shin, S. E. Ahnert, J. Park
Ranking Competitors Using Degree-Neutralized Random Walks
PLOS ONE 9(12): e113685 (2014)
G. F. Chami, S. E. Ahnert, M. J. Voors, A. A. Kontoleon
Social Network Analysis Predicts Health Behaviours and Self-Reported Health in African Villages
PLOS ONE 9(7): e103500 (2014)
R. Ahnert, S. E. Ahnert
A community under attack: Protestant letter networks in the reign of Mary I
Leonardo 47, 275 (2014)
S. E. Ahnert
Generalised power graph compression reveals dominant relationship patterns in complex networks
Scientific Reports 4, 4385 (2014)
S. F. Greenbury, I. G. Johnston, A. A. Louis, S. E. Ahnert
A tractable genotype-phenotype map modelling the self-assembly of protein quaternary structure
Journal of The Royal Society Interface 11, 20140249 (2014)
S. E. Ahnert
Power graph compression reveals dominant relationships in genetic transcription networks
Molecular BioSystems 9, 2681 (2013)
D. Garlaschelli, S. E. Ahnert, T. Fink, G. Caldarelli
Low-Temperature Behaviour of Social and Economic Networks
Entropy 15, 3148 (2013)
Y.-Y. Ahn, S. E. Ahnert
The Flavor Network
Leonardo 46, 272 (2013)
J. A. Marsh, H. Hernandez, Z. Hall, S. E. Ahnert, T. Perica, C. V. Robinson, S. A. Teichmann
Protein complexes are under evolutionary selection to assemble via ordered pathways
Cell 153, 461 (2013)
E. K. Towlson, P. Vertes, S. E. Ahnert, W. Schafer, E. Bullmore
The rich club of the C. elegans neuronal connectome
Journal of Neuroscience 33, 6380 (2013)
S. E. Ahnert
Network analysis and data mining in food science: the emergence of computational gastronomy
Flavour 2:4 (2013)
T. Perica, J. A. Marsh, F. L. Sousa, E. Natan, L. J. Colwell, S. E. Ahnert, S. A. Teichmann
The emergence of protein complexes: quaternary structure, dynamics and allostery
Biochem. Soc. Trans. 40, 475 (2012)
Y. Y. Ahn, S. E. Ahnert, J. P. Bagrow, A.-L. Barabási
Flavor network and the principles of food pairing
Scientific Reports 1:196 (2011)
I. G. Johnston, S. E. Ahnert, J. P. K. Doye, A. A. Louis
Evolutionary dynamics in a simple model of self-assembly
Physical Review E 83, 066105 (2011)
S. M. Brady, L. Zhang, M. Megraw, N. J. Martinez, E. Jiang, C. S. Yi, W. Liu, A. Zeng, M. Taylor-Teeples, D. Kim, S. E. Ahnert, U. Ohler, D. Ware, A. J. M. Walhout, P. N. Benfey
A stele-enriched gene regulatory network in the Arabidopsis root
Molecular Systems Biology, 7:459 (2011)
M. A. Moreno-Risueno, J. M. Van Norman, A. Moreno, J. Zhang, S. E. Ahnert, P. N. Benfey
Oscillating Gene Expression Determines Competence for Periodic Arabidopsis Root Branching
Science 329, 1306 (2010)
S. E. Ahnert, I. G. Johnston, T. M. A. Fink, J. P. K. Doye, A. A. Louis
Self-assembly, modularity and physical complexity
Physical Review E 82, 026117 (2010)
D. A. Orlando, S. M. Brady, T. M. A. Fink, P. N. Benfey, S. E. Ahnert
Detecting separate time scales in genetic expression data
BMC Genomics 11:381 (2010)
S. E. Ahnert, B. A. N. Travencolo, L. da Costa Fontoura
Connectivity and dynamics of neuronal networks as defined by the shape of individual neurons
New Journal of Physics 11, 103053 (2009)
J. B. Coe, S. E. Ahnert, T. M. A. Fink
When are cellular automata random?
Europhysics Letters 84, 50005 (2008)
S. E. Ahnert, S. A. Teichmann
Networks for all
Genome Biology 9, 324 (2008)
S. E. Ahnert, T. M. A. Fink
Clustering signatures classify directed networks
Physical Review E 78, 036112 (2008)
T. M. A. Fink, J. B. Coe, S. E. Ahnert
Single-elimination competition
Europhysics Letters 83, 60010 (2008)
M.-L. Dequeant, S. E. Ahnert, H. Edelsbrunner, T. M. A. Fink, Y. Mileyko, J. Morton, A. R. Mushegian, L. Pachter, M. Rowicka, A. Shiu, B. Sturmfels, O. Pourquie
Comparison of Pattern Detection Methods in Microarray Time Series of the Segmentation Clock
PLOS ONE 3(8): e2856 (2008)
S. E. Ahnert, D. Garlaschelli, T. M. A. Fink, G. Caldarelli
Applying weighted network measures to microarray distance matrices
Journal of Physics A 41, 224011 (2008)
S. E. Ahnert, T. M. A. Fink, A. Zinovyev
How much non-coding DNA do eukaryotes require?
Journal of Theoretical Biology 252, 587 (2008)
S. E. Ahnert, D. Garlaschelli, T. M. A. Fink, G. Caldarelli
An ensemble approach to the analysis of weighted networks
Physical Review E 76, 016101 (2007)
S. E. Ahnert, K. Willbrand, F. C. S. Brown, T. M. A. Fink
Unbiased pattern detection in microarray data series
Bioinformatics 22, 1471 (2006)
S. E. Ahnert, M. C. Payne
All possible bipartite positive-operator-value measurements of two-photon polarization states
Physical Review A 73, 022333 (2006)
S. E. Ahnert, M. C. Payne
General implementation of all possible positive-operator-value measures of single photon polarization states
Physical Review A 71, 012330 (2005)
S. E. Ahnert, M. C. Payne
Linear optics implementation of weak values in Hardy's paradox
Physical Review A 70, 042102 (2004)
S. E. Ahnert, M. C. Payne
Weak measurement of the arrival times of single photons and pairs of entangled photons
Physical Review A 69, 042103 (2004)
S. E. Ahnert, M. C. Payne
Nonorthogonal projective positive-operator-value measurement of photon polarization states with unit probability of success
Physical Review A 69, 012312 (2004)
I have given two graduate lecture courses on the following topics:
Complex Networks - Slides can be
found here.
Quantum Information Theory - Lecture notes can be
found here.
Current graduate students:
Paula Garcia Galindo (PhD)
Runfeng Lin (PhD)
Sung Soo Moon (PhD)
William Lowe (PhD)
Nicholas Katritsis (PhD)
Former postdoctoral researchers:
Yavor Novev
Former graduate students:
Chun Wan (Part III)
Runfeng Lin (MPhil)
Nora Martin (PhD)
Marcel Weiß (PhD)
Alexander Leonard (PhD)
Will Grant (PhD)
Yuanyie Chen (PhD, co-supervised)
Alexander Johnston (MPhil)
Salvatore Tesoro (PhD)
Emma Towlson (PhD)
Sam Greenbury (PhD)
Pascal Grobecker (Part III)
Former undergraduate students:
Elliot Vaughan (CET IIB project)
James Simkins (CET IIB project)
Former summer students:
Isabelle Kekwick
Reina Zheng
Fátima González
Toby Baker
Marijana Vujadinović
Pranav Reddy
Eniak Alarcón
Giles Barton-Owen
Laura Imperatori
Robert Baldock
Some of my collaborators, past and present:
Yong-Yeol Ahn
Ruth Ahnert
Albert-László Barabási
Siobhan Brady
Ed Bullmore
Guido Caldarelli
Gábor Csányi
Thomas Fink
Howard Hotson
Iain Johnston
Ard Louis
Mike Payne
Chris Pickard
Sarah Teichmann
Andrei Zinovyev
Links to pages on various scientific and non-scientific topics.
BiProjector - an online tool for projecting bipartite networks
Imbrella - A free and invisible umbrella
How to play Go on a Hypercube
John Baez's Homepage
The Chocolate Revolution
The biggest number
The Clay Millenium Prize
The Klein Bottle Shop
The Complexity Zoo
Non-Transitive Dice
Non-Transitive Lizards
'Math In LaTeX'
The CSS Zen Garden
The Simulation Argument
Minds, Machines and Gödel by John Lucas
Robert J. Lang's Origami Designs
The elgooG Google mirror
Iocaine Powder
57 Optical Illusions
Puzzles