Laurence Loewe

Laurence Loewe
Assistant Professor
330 North Orchard Street
Madison WI 53715
Room 3164
(608) 316-4324, (608) 316-4326
Developing a stable, user-friendly programming language compiler for reproducible biodata analyses and general modeling in biology while building in-depth models for bioresearch

Years at WID

2010 - present


Naming Fun
Naming is hard. In fact it is one of the hardest problems in biology, computer science, math, etc., and also the most costly activity in the Loewe Lab so far. Hence the lab's research on naming. For example, we defined the data type 'BioBinary'. In a funny twist of fate, the name of the PI ('Loewe') is rarely pronounced correctly. The PI doesn't care, as long as the semantics is clear: 'Loewe' is German for 'Lion'.


  • Jugend Forscht (similar to US Science Talent Search), extensive, self-directed research on Miller-Urey chemical evolution experiments, supported by several departments from different disciplines at the University of Erlangen, Germany; 5 competitions, 1987-1991.
  • Biology MSc-equiv., focus on molecular aspects, experiments, University of Konstanz, Germany, 1995.
  • Dr. rer. nat., Microbiology, Muller's ratchet, evolution@home, Technical University of Munich, Germany, 2002.
  • Postdoc in theoretical population genetics, University of Edinburgh, UK, 2003-2006.
  • Lecturer in Evolutionary Genetics (sabbatical replacement), University of Edinburgh, UK
  • Postdoc in process algebra modelling and quantitative analysis, focus on molecular systems biology, CSBE, Laboratory for Foundations of Computer Science, University of Edinburgh, UK, 2007-2010.


Research Description

Nothing in biology makes sense except when properly quantified in the light of evolution.

From antibiotics resistance evolution and cancer to species extinction, evolution governs many challenges we face today; finding ways forward often requires causal insights from mechanistic models.

The Loewe Lab aims to improve the quality of diverse biological models by quantifying evolution with increasing precision. This inspired the PI to estimate the strength of selection in population genetics models from DNA sequence analyses and mutation accumulation experiments, approaches that struggle to quantify many types of mutational effects. Thus, Loewe investigates how to analyze molecular systems biology models from a population genetics view. He defined a framework for mechanistic evolutionary systems biology, which facilitates exploring mechanistic fitness landscapes by the versatile composition and analysis of complex biological simulation models.

To meet these challenging modeling demands, Loewe initiated the development of Evolvix, a modeling language he is designing to simplify mathematically accurate descriptions of concurrent systems that change over time. Such systems are often studied in biology, from biochemical reaction networks to evolving ecological webs. He develops a programming language architecture that integrates his 20+ years of experience in computational biology, in order to make Evolvix as user-friendly and as stable as possible. This work has inspired searching across disciplines for the best abstractions available for assisting biologists in navigating the complexity and diversity of biological systems. The Loewe Lab implemented a prototype of Evolvix that is currently used in the evolutionary systems biology modeling introduction course, which he developed at UW-Madison (Genetics 546).

Work with this prototype and in-depth usability reviews convinced Loewe that biology needs a dedicated general-purpose programming language designed by biologists for biologists. He develops formalisms and concepts for extending Evolvix accordingly without compromising its user-friendliness, which required a new approach to designing programming language architecture. As simulating evolution can quickly challenge any big computer, he is integrating Evolvix with evolution@home, the first globally distributed computing system for evolutionary biology that he started in 2001.

To keep Evolvix development relevant for working biologists, the in silico Loewe Lab also engages with a broad range of in-depth biological research to provide opportunities for testing on real-world problems. Such work includes building relevant Evolvix simulation models and the biodata science required for curating realistic model parameters. Research in his lab has investigated circadian clocks in flies, cholesterol biosynthesis, how selection shapes genomes, growing cancer cells, stochasticity in the evolution of cooperative behavior in game theory, potential genetic causes for species extinction, the evolution of antibiotics resistance, and more.

In-depth research with these models has also led to rich interactions with related theories for modeling, inspiring abstract aspects of compiler construction and contributing to the modeling framework developed for Evolvix. It also resulted in new perspectives on reproducibility, biosystems curation, biodata science, statistical logic, and the formal computing tools that are required for enabling biologists of the future to more efficiently learn from past results, positive or negative, in order to better build on today’s biological data and results (see FlyClockbase, 2017).

The ability to build efficiently and reproducibly on existing computational results is key to solving many biological problems with a practical impact.

More details can be found on the

Annual EvoSysBio Meetings

Loewe organized EvoSysBio meetings in various forms and maintains the most complete curated list of past meetings in evolutionary systems biology. Entries are added as new meetings become known.

If you know about an EvoSysBio meeting that should be listed or would like to contribute to an upcoming meeting, get into contact.

Interested in the Loewe Lab?

Interested in working on modeling, biosystems curation, or reproducibility in the Loewe Lab? Ready for in silico biology, but can’t program? Not scared about improving names for concepts or exploring semantics in-depth? Interactive writing support sounds cool? If you have the tenacity to work and learn in the heat where concepts for tomorrow are being forged, specify what you look for, what you bring to the lab, and why the lab is a great fit. Argue well and you might earn an interview; but be warned, the Lab builds biodata science tools for the professional biosystems curators of tomorrow. To speed them up, some steps today need slow-motion analysis or very advanced programming skills. Breaking new ground is not fast. So, most computational biology is more fun elsewhere, your industry experience in C++, CMake, node.js etc., deserves what the Lab can’t pay, and you need to get the MOs in the Lab’s (2017) BESTnames paper to program here.

Yet, this unusual Lab thrives on synergies between its members’ special skills for its own ‘Mission Impossible’. Do your hidden talents fit now? Impossible to predict. Apply with all details you want to share, so the Lab can reply as opportunities appear. Some may require that you are self-funded, or can volunteer time, or enroll in a special course, or find a training grant (see below), or that the Lab has funds. An easy way to learn more about the type of modeling work done in the Lab is to attend the evolutionary systems biology modeling introduction course, (Genetics 546).

Teaching Innovation


The Loewe Lab regularly participates at these events:

If you are interested in organizing a special outreach event that involves modeling some aspects in biology or other aspects of our work, do not hesitate to contact the LoeweLab.

For extending outreach activities, the Loewe Lab is looking for a middle-school or high-school teacher interested in the (paid) summer work of developing the materials for more efficiently teaching high-school students about modeling by using the Evolvix platform developed in the lab. 


The Loewe Lab at the University of Wisconsin-Madison is affiliated with:

PhD students in the following training programs can join the lab more easily than others:


NSF Career Award (2012) Modeling made easy: Extending systems biology modeling approaches to genetics and ecology

Selected Publications

Search Pubmed for more publications by Laurence Loewe:

  • McLoone B, Fan W-T L, Pham A, Smead R, and Loewe L (2018) “Stochasticity, Selection, and the Evolution of Cooperation in a Two-Level Moran Model of the Snowdrift Game”, Complexity, in press, Article ID 9836150   -   Link to DOI
  • Warren, Wesley C, García-Pérez R, Xu S, Lampert KP, Chalopin D, Stöck M, Loewe L, Lu Y, Kuderna L, Minx P, Montague MJ, Tomlinson C, Hillier LW, Murphy DN, Wang J, Wang Z, Garcia CM, Thomas GCW, Volff J-N, Farias F, Aken B, Walter RB, Pruitt KD, Marques-Bonet T, Hahn MW, Kneitz S, Lynch L & Schartl M (2018) “Clonal polymorphism and high heterozygosity in the celibate genome of the Amazon molly”, Nature Ecology & Evolution (online advance publication)   -   Link to DOI   -   Press coverage: BBC
  • Scheuer KS, Hanlon B, Dresel JW, Nolan ED, Davis JC, Loewe L (2017) “FlyClockbase: Importance of Biosystems Curation for Analyzing Variability in Circadian Clock of Drosophila melanogaster by Integrating Time Series from 25 Years of Research
  • [book-length discussion of circadian clock biodata science that is currently being transformed into a series of reports for a special issue]   -   Link to BioRxiv DOI
  • Loewe L, Scheuer KS, Keel SA, Vyas V, Liblit B, Hanlon B, Ferris MC , Yin J, Dutra I, Pietsch A, Javid CG, Moog CL, Meyer J, Dresel J, McLoone B, Loberger S, Movaghar A, Gilchrist-Scott M, Sabri Y, Sescleifer D, Pereda-Zorrilla I, Zietlow A, Smith R, Pietenpol S, Goldfinger J, Atzen SL, Freiberg E, Waters NP, Nusbaum C, Nolan E, Hotz A, Kliman RM, Mentewab A, Fregien N, Loewe M  (2017) “Evolvix BEST Names for semantic reproducibility across code2brain interfacesAnn. New York Acad. Sci. 1387:124-144   -   Link to DOI  for updates see  and more on the POSTsystem
  • Loewe L (2016) “Systems in Evolutionary Systems Biology”, pp. 297-318, vol. 4, in Encyclopedia of Evolutionary Biology, ed.: Richard M. Kliman, Oxford, UK, Academic Press. doi:10.1016/B978-0-12-800049-6.00184-0   -   Link to PDF
  • James D, et al. (2014) "Standing Together for Reproducibility in Large-Scale Computing: Report on reproducibility@XSEDE"   -
  • Loewe L (2015) “EvoSysBio in 10 Slides”,   -   Link to DOI
  • Loewe L (2015) “EvoSysBio LIFTs: Microbes and Antibiotics”,   -   Link to DOI
  • Ehlert, K and Loewe L (2014) "Lazy Updating of hubs can enable more realistic models by speeding up stochastic simulations". Journal of Chemical Physics 141:204109, 20 pages   -   Links to DOI
  • McGaugh SE, Heil CSS, Manzano-Winkler B, Loewe L, Goldstein S, Himmel TL, and Noor MAF (2012) "Recombination modulates how selection affects linked sites in drosophila". PLoS Biology 10(11): e1001422, 17 pages. PMCID: PMC3496668   -   Link to DOI
  • Modrzynska K, Creasey A, Loewe L, Cezard T, Martinelli A, Borges S, Cravo P, Blaxter M, CarterR, and Hunt P (2012) “Genome-wide re-sequencing defines mutations of complex chloroquine resistance in malaria”. BMC Genomics 13:106, 16 pages    -   Link to DOI
  • Loewe L, Guerriero ML, Watterson S, Moodie S, Ghazal P and Hillston, J (2011) “Translation from the quantified implicit process flow abstraction in SBGN-PD diagrams to Bio-PEPA illustrated on the cholesterol pathway”, Lecture Notes in Computer Science LNCS vol. 6575, pages 13-38   -   Link to DOI
  • Loewe L and Hill, WG (2010) “Introduction: The population genetics of mutations: good, bad and indifferent”. Philosophical Transactions of the Royal Society Series B
  • vol. 365:1153-1167   -   Link to DOI
  • Akman OE, Guerriero M-L, Loewe L and Troein C (2010) “Complementary approaches to understanding the plant circadian clock”, Electronic Proceedings in Theoretical Computer Science (EPTCS) 19:1–19   -   Link to DOI
  • Loewe L, Moodie S and Hillston J (2009) "Quantifying the implicit process flow abstraction in SBGN-PD diagrams with Bio-PEPA”, Electronic Proceedings in Theoretical Computer Science (EPTCS) 6:93-107   -   Link to DOI   -   Builds a compiler to build a bridge from visual model construction to automated simulations.
  • Loewe L (2009) "A framework for evolutionary systems biology". BMC Systems Biology 3:27, 34 pages,   -   Link to DOI
  • Loewe L and Hillston J (2008) "The distribution of mutational effects on fitness in a simple circadian clock", CMSB08, Lecture Notes in Bioinformatics 5307:156-175   -   Link to DOI
  • Loewe L and Lamatsch D (2008) "Quantifying the threat from Muller's ratchet in the Amazon molly (Poecilia formosa)". BMC Evolutionary Biology 8:88, 20 pages   -   Link to DOI
  • Loewe L (2007) "Evolution@home: observations on participant choice, work unit variation and low-effort global computing". Softw. Pract. & Exp. 37:1289-1318   -   Link to DOI
  • Loewe L and Charlesworth B (2007) "Background selection in single genes may explain patterns of codon bias". Genetics 175:1381-1393   -   Link to DOI
  • Loewe L and Charlesworth B (2006) "Inferring the distribution of mutational effects on fitness in Drosophila". Biology Letters 2:426-430   -   Link to DOI
  • Loewe L (2006) "Quantifying the genomic decay paradox due to Muller's ratchet in human mitochondrial DNA". Genetical Research 87:133-159   -   Link to DOI
  • Loewe L, Charlesworth B, Bartolomé C and Nöel V (2006) "Estimating selection on non-synonymous mutations". Genetics 172:1079-1092   -   Link to DOI
  • Loewe L, Textor V and Scherer S (2003) "High deleterious genomic mutation rate in stationary phase of Escherichia coli". Science 302:1558-1560   -   Link to DOI
  • Loewe L (2002) "Global computing for bioinformatics".
  • Briefings in Bioinformatics 3:377-388   -   Link to DOI