© Leibniz-Institut (IPK)


The Network Analysis and Modelling group is devoted to investigate molecular mechanisms of phenotype emergence in crops by means of large-scale data integration on the genomic, transcriptomic, metabolomic, and phenomic level. In practical terms, we develop and implement machine learning approaches and network analysis algorithms that help us (or others) to discover new gene functions, or new interactions between genes, metabolites and phenotypes.

Some of our specific activities include e.g. implementations of Deep Learning for crops phenotype prediction and breeding, motif discovery in large multi-omic genome-to-phenome networks, and “gamification” of plant development. Our favourite crops include cereals but we have special affinity to solanaceous plants too. Furthermore, we provide statistical expertise, machine learning solutions, and data visualisation tools for interpretation of high-throughput data in IPK.

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Blätke M-A, Beier S, Scholz U, Gladilin E, Szymanski J J (Eds.):

Front. Plant Sci., Frontiers Research Topics “Advances in Applied Bioinformatics in Crops." Lausanne: Frontiers Media SA (2021) dx.doi.org/10.3389/978-2-88966-620-1

Blätke M-A, Szymanski J J, Gladilin E, Scholz U, Beier S:

Editorial: Advances in applied bioinformatics in crops. Front. Plant Sci. 12 (2021) 640394. https://dx.doi.org/10.3389/fpls.2021.640394

Municio C, Antosz W, Grasser K, Kornobis E, van Bel M, Eguinoa I, Coppens F, Bräutigam A, Lermontova I, Bruckmann A, Zelkowska K, Houben A, Schubert V:

The Arabidopsis condensin CAP-D subunits arrange interphase chromatin. New Phytol. 230 (2021) 972-987. https://dx.doi.org/10.1111/nph.17221

Panda S, Jozwiak A, Sonawane P D, Szymanski J, Kazachkova Y, Vainer A, Vasuki H, Almekias-Siegl E, Dikaya V, Bocobza S, Shohat H, Meir S, Wizler G, Giri A P, Schuurink R, Weiss D, Yasuor H, Kamble A, Aharoni A:

Steroidal alkaloids defense metabolism and plant growth are modulated by the joint action of gibberellin and jasmonate signaling. New Phytol. (2021) Epub ahead of print. dx.doi.org/10.1111/nph.17845

Sahu A, Blätke M-A, Szymański J J, Töpfer N:

Advances in flux balance analysis by integrating machine learning and mechanism-based models. Comput. Struct. Biotechnol. J. 19 (2021) 4626-4640. https://doi.org/10.1016/j.csbj.2021.08.004


Forbang Peleke F:

Impact of genetic variation on the activity of gene promoters in Arabidopsis thaliana - Deep learning meets plant genomics. (Master Thesis) Mittweida, Hochschule Mittweida, Fakultät Angewandte Computer- und Biowissenschaften (2020)

Korenblum E, Dong Y, Szymanski J, Panda S, Jozwiak A, Massalha H, Meir S, Rogachev I, Aharoni A:

Rhizosphere microbiome mediates systemic root metabolite exudation by root-to-root signaling. Proc. Natl. Acad. Sci. U.S.A. 117 (2020) 3874-3883. https://dx.doi.org/10.1073/pnas.1912130117

Psaroudakis D, Liu F, König P, Scholz U, Junker A, Lange M, Arend D:

isa4j: a scalable Java library for creating ISA-Tab metadata [version 1; peer review: 2 approved]. F1000Research 9(ELIXIR) (2020) 1388. https://doi.org/10.12688/f1000research.27188.1

Stock J, Bräutigam A, Melzer M, Bienert G P, Bunk B, Nagel M, Overmann J, Keller E R J, Mock H P:

The transcription factor WRKY22 is required during cryo-stress acclimation in Arabidopsis shoot tips. J. Exp. Bot. 71 (2020) 4993-5009. https://dx.doi.org/10.1093/jxb/eraa224

Szymański J, Bocobza S, Panda S, Sonawane P, Cárdenas P D, Lashbrooke J, Kamble A, Shahaf N, Meir S, Bovy A, Beekwilder J, Tikunov Y, Romero de la Fuente I, Zamir D, Rogachev I, Aharoni A:

Analysis of wild tomato introgression lines elucidates the genetic basis of transcriptome and metabolome variation underlying fruit traits and pathogen response. Nat. Genet. 52 (2020) 1111-1121. https://dx.doi.org/10.1038/s41588-020-0690-6

Treves H, Siemiatkowska B, Luzarowska U, Murik O, Fernandez-Pozo N, Moraes T A, Erban A, Armbruster U, Brotman Y, Kopka J, Rensing S A, Szymanski J, Stitt M:

Multi-omics reveals mechanisms of total resistance to extreme illumination of a desert alga. Nat. Plants 6 (2020) 1031-1043. https://dx.doi.org/10.1038/s41477-020-0729-9


Blätke M A, Bräutigam A:

Evolution of C4 photosynthesis predicted by constraint-based modelling. eLife 8 (2019) e49305. https://dx.doi.org/10.7554/eLife.49305

Cárdenas P D, Sonawane P D, Heinig U, Jozwiak A, Panda S, Abebie B, Kazachkova Y, Pliner M, Unger T, Wolf D, Ofner I, Vilaprinyo E, Meir S, Davydov O, Gal-On A, Burdman S, Giri A, Zamir D, Scherf T, Szymanski J, Rogachev I, Aharoni A:

Pathways to defense metabolites and evading fruit bitterness in genus Solanum evolved through 2-oxoglutarate-dependent dioxygenases. Nat. Commun. 10 (2019) 5169. https://dx.doi.org/10.1038/s41467-019-13211-4

Cohen H, Dong Y, Szymanski J, Lashbrooke J, Meir S, Almekias-Siegl E, Zeisler-Diehl V V, Schreiber L, Aharoni A:

A multilevel study of melon fruit reticulation provides insight into skin ligno-suberization Hallmarks. Plant Physiol. 179 (2019) 1486-1501. https://dx.doi.org/10.1104/pp.18.01158

Meyer R C, Gryczka C, Neitsch C, Müller M, Bräutigam A, Schlereth A, Schön H, Weigelt-Fischer K, Altmann T:

Genetic diversity for nitrogen use efficiency in Arabidopsis thaliana. Planta 250 (2019) 41–57. https://dx.doi.org/10.1007/s00425-019-03140-3


Blätke M A:

BioModelKit - an integrative framework for multi-scale biomodel-engineering. J. Integr. Bioinform. 15 (2018) 20180021. https://dx.doi.org/10.1515/jib-2018-0021

Blätke M-A, Rohr C:

BioModelKit: spatial modelling of complex multiscale molecular biosystems based on modular models. Fundamenta Informaticae 160 (2018) 221-254. https://dx.doi.org/10.3233/FI-2018-1682

Ramírez-González R H, Borrill P, Lang D, Harrington S A, Brinton J, Venturini L, Davey M, Jacobs J, van Ex F, Pasha A, Khedikar Y, Robinson S J, Cory A T, Florio T, Concia L, Juery C, Schoonbeek H, Steuernagel B, Xiang D, Ridout C J, Chalhoub B, Mayer K F X, Benhamed M, Latrasse D, Bendahmane A, Wulff B B H, Appels R, Tiwari V, Datla R, Choulet F, Pozniak C J, Provart N J, Sharpe A G, Paux E, Spannagl M, Bräutigam A, Uauy C:

The transcriptional landscape of polyploid wheat. Science 361 (2018) eaar6089. https://dx.doi.org/10.1126/science.aar6089

Saper G, Kallmann D, Conzuelo F, Zhao F, Toth T N, Liveanu V, Meir S, Szymanski J, Aharoni A, Schuhmann W, Rothschild A, Schuster G, Adir N:

Live cyanobacteria produce photocurrent and hydrogen using both the respiratory and photosynthetic systems. Nat. Commun. 9 (2018) 2168. https://dx.doi.org/10.1038/s41467-018-04613-x


Bräutigam A, Eisenhut M, Schlüter U, Gowik U:

On the evolutionary origin of CAM photosynthesis. Plant Physiol. 174 (2017) 473-477. https://dx.doi.org/10.1104/pp.17.00195

Brouwer P, Bräutigam A, Buijs V A, Tazelaar A O E, van der Werf A, Schlüter U, Reichart G J, Bolger A, Usadel B, Weber A P M, Schluepmann H:

Metabolic adaptation, a specialized leaf organ structure and vascular responses to diurnal N2 fixation by Nostoc azollae sustain the astonishing productivity of Azolla ferns without nitrogen fertilizer. Front. Plant Sci. 8 (2017) 442. https://dx.doi.org/10.3389/Fpls.2017.00442

Denton A K, Mass J, Kulahoglu C, Lercher M J, Bräutigam A, Weber A P:

Freeze-quenched maize mesophyll and bundle sheath separation uncovers bias in previous tissue-specific RNA-Seq data. J. Exp. Bot. 68 (2017) 147-160. https://dx.doi.org/10.1093/jxb/erw463

Eisenhut M, Bräutigam A, Timm S, Florian A, Tohge T, Fernie A R, Bauwe H, Weber A P M:

Photorespiration is crucial for dynamic response of photosynthetic metabolism and stomatal movement to altered CO2 availability. Mol. Plant 10 (2017) 47-61. https://dx.doi.org/10.1016/j.molp.2016.09.011

König S, Eisenhut M, Bräutigam A, Kurz S, Weber A P M, Büchel C:

The influence of a cryptochrome on the gene expression profile in the diatom Phaeodactylum tricornutum under blue light and in darkness. Plant Cell Physiol. 58 (2017) 1914-1923. https://dx.doi.org/10.1093/pcp/pcx127

Rademacher N, Wrobel T J, Rossoni A W, Kurz S, Bräutigam A, Weber A P M, Eisenhut M:

Transcriptional response of the extremophile red alga Cyanidioschyzon merolae to changes in CO2 concentrations. J. Plant Physiol. 217 (2017) 49-56. https://dx.doi.org/10.1016/j.jplph.2017.06.014

Schlüter U, Bräutigam A, Gowik U, Melzer M, Christin P-A, Kurz S, Mettler-Altmann T, Weber A P:

Photosynthesis in C3–C4 intermediate Moricandia species. J. Exp. Bot. 68 (2017) 191-206. https://dx.doi.org/10.1093/jxb/erw391

Thirulogachandar V, Alqudah A M, Koppolu R, Rutten T, Graner A, Hensel G, Kumlehn J, Bräutigam A, Sreenivasulu N, Schnurbusch T, Kuhlmann M:

Leaf primordium size specifies leaf width and vein number among row-type classes in barley. Plant J. 91 (2017) 601-612. https://dx.doi.org/10.1111/tpj.13590


Bräutigam A, Gowik U:

Photorespiration connects C3 and C4 photosynthesis. J. Exp. Bot. 67 (2016) 2953-2962. https://dx.doi.org/10.1093/jxb/erw056

Döring F, Streubel M, Bräutigam A, Gowik U:

Most photorespiratory genes are preferentially expressed in the bundle sheath cells of the C4 grass Sorghum bicolor. J. Exp. Bot. 67 (2016) 3053-3064. https://dx.doi.org/10.1093/jxb/erw041

Schlüter U, Denton A K, Bräutigam A:

Understanding metabolite transport and metabolism in C4 plants through RNA-seq. Curr. Opin. Plant Biol. 31 (2016) 83-90. https://dx.doi.org/10.1016/j.pbi.2016.03.007

Xu J, Bräutigam A, Li Y, Weber A P M, Zhu X-G:

Systems analysis of cis-regulatory motifs in C4 photosynthesis genes using maize and rice leaf transcriptomic data during a process of de-etiolation. J. Exp. Bot. 67 (2016) 5105-5117. https://dx.doi.org/10.1093/jxb/erw275

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