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Article: TraqBio - Flexible Progress Tracking for Core Unit Projects

Kestler, Hans

PLOS ONE, 11(9):e0162857

2016

Abstract: MOTIVATION: Core service units have become an organisational hallmark in many research institutions world wide. Such service cores provide complex state-of-the-art technologies and expertise to the research community. Typically, a user delivers material ... ...

Institution	Leibniz-Institut für Alternsforschung
Abstract	MOTIVATION: Core service units have become an organisational hallmark in many research institutions world wide. Such service cores provide complex state-of-the-art technologies and expertise to the research community. Typically, a user delivers material or raw data to a core. The core defines work packages for ensuing analysis and returns results back to the user. This core activity can be quite complex and time consuming and usually does not communicate itself to the outside. Naturally, the user is highly interested to follow the progress of a project once handed over to the core unit. This generates a time-intensive direct communication activity back and forth. A more effective, convenient and less disruptive way to track the status of a given project by the researcher, but also by core managers, appears highly desirable. Hence, we developed a lightweight and readily implementable web application that allows efficient progress tracking of core unit projects. RESULTS: The web application TraqBio allows for the convenient tracking of projects. Following project set-up by the core, the user receives an e-mail containing links for tracking the project status. Examples are provided for three common core units, namely genomics, proteomics, and bioinformatics units. TraqBio is a secure lightweight web application that can be either used in a standalone setup or incorporated into an existing web server infrastructure. Being accessible not only from classical desktop computers but also from mobile devices such as smartphones and tablets, TraqBio offers easy integration into every day work.
Keywords	Cell phones ; Bioinformatics ; Genome analysis ; Genome complexity ; Genomics ; Genomic libraries ; Proteomics ; Web-based applications
Language	English
Document type	Article
Database	Repository for Life Sciences

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Article: 3D Network exploration and visualisation for lifespan data

Platzer, Matthias / Kestler, Hans

BMC bioinformatics, 19:390

2018

Abstract: BACKGROUND: The Ageing Factor Database AgeFactDB contains a large number of lifespan observations for ageing-related factors like genes, chemical compounds, and other factors such as dietary restriction in different organisms. These data provide ... ...

Institution	Leibniz-Institut für Alternsforschung
Abstract	BACKGROUND: The Ageing Factor Database AgeFactDB contains a large number of lifespan observations for ageing-related factors like genes, chemical compounds, and other factors such as dietary restriction in different organisms. These data provide quantitative information on the effect of ageing factors from genetic interventions or manipulations of lifespan. Analysis strategies beyond common static database queries are highly desirable for the inspection of complex relationships between AgeFactDB data sets. 3D visualisation can be extremely valuable for advanced data exploration. RESULTS: Different types of networks and visualisation strategies are proposed, ranging from basic networks of individual ageing factors for a single species to complex multi-species networks. The augmentation of lifespan observation networks by annotation nodes, like gene ontology terms, is shown to facilitate and speed up data analysis. We developed a new Javascript 3D network viewer JANet that provides the proposed visualisation strategies and has a customised interface for AgeFactDB data. It enables the analysis of gene lists in combination with AgeFactDB data and the interactive visualisation of the results. CONCLUSION: Interactive 3D network visualisation allows to supplement complex database queries by a visually guided exploration process. The JANet interface allows gaining deeper insights into lifespan data patterns not accessible by common database queries alone. These concepts can be utilised in many other research fields.
Keywords	3D visualization ; AgeFactDB ; Ageing ; Ageing factor database ; Gene network ; Differentially expressed genes ; Lifespan
Language	English
Document type	Article
Database	Repository for Life Sciences

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Article: Long-lived rodents reveal signatures of positive selection in genes associated with lifespan

Bens, Martin / Holtze, Susanne / Groth, Marco / Kestler, Hans / Cellerino, Alessandro / Platzer, Matthias

PLOS ONE, 14(3):e1007272

2018

Abstract: The genetics of lifespan determination is poorly understood. Most research has been done on short-lived animals and it is unclear if these insights can be transferred to long-lived mammals like humans. Some African mole-rats (Bathyergidae) have life ... ...

Institution	Leibniz-Institut für Zoo- und Wildtierforschung (Berlin) Leibniz-Institut für Alternsforschung
Abstract	The genetics of lifespan determination is poorly understood. Most research has been done on short-lived animals and it is unclear if these insights can be transferred to long-lived mammals like humans. Some African mole-rats (Bathyergidae) have life expectancies that are multiple times higher than similar sized and phylogenetically closely related rodents. To gain new insights into genetic mechanisms determining mammalian lifespans, we obtained genomic and transcriptomic data from 17 rodent species and scanned eleven evolutionary branches associated with the evolution of enhanced longevity for positively selected genes (PSGs). Indicating relevance for aging, the set of 250 identified PSGs showed in liver of long-lived naked mole-rats and short-lived rats an expression pattern that fits the antagonistic pleiotropy theory of aging. Moreover, we found the PSGs to be enriched for genes known to be related to aging. Among these enrichments were “cellular respiration” and “metal ion homeostasis”, as well as functional terms associated with processes regulated by the mTOR pathway: translation, autophagy and inflammation. Remarkably, among PSGs are RHEB, a regulator of mTOR, and IGF1, both central components of aging-relevant pathways, as well as genes yet unknown to be aging-associated but representing convincing functional candidates, e.g. RHEBL1, AMHR2, PSMG1 and AGER. Exemplary protein homology modeling suggests functional consequences for amino acid changes under positive selection. Therefore, we conclude that our results provide a meaningful resource for follow-up studies to mechanistically link identified genes and amino acids under positive selection to aging and lifespan determination.
Language	English
Document type	Article
Database	Repository for Life Sciences

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Article: Comment on 'Naked mole-rat mortality rates defy Gompertzian laws by not increasing with age'

Dammann, Philip / Scherag, André / Zak, Nikolay / Szafranski, Karol / Holtze, Susanne / Begall, Sabine / Kestler, Hans A. / Hildebrandt, Thomas Bernd / Platzer, Matthias

eLife, 8:e45415

2019

Abstract: Ruby et al. recently analyzed historical lifespan data on more than 3200 naked mole-rats, collected over a total observation period of about 38 years (Ruby et al., 2018). They report that mortality hazards do not seem to increase across the full range of ...

Institution	Leibniz-Institut für Zoo- und Wildtierforschung (Berlin) Leibniz-Institut für Alternsforschung
Abstract	Ruby et al. recently analyzed historical lifespan data on more than 3200 naked mole-rats, collected over a total observation period of about 38 years (Ruby et al., 2018). They report that mortality hazards do not seem to increase across the full range of their so-far-observed lifespan, and conclude that this defiance of Gompertz's law ‘uniquely identifies the naked mole-rat as a non-aging mammal’. Here, we explain why we believe this conclusion is premature.
Keywords	AGING ; BATHYERGIDAE ; GOMPERTZ ; ECOLOGY ; LONGEVITY ; MAMMALS ; NAKED MOLE-RAT ; SCIENTIFIC CORRESPONDENCE
Language	English
Document type	Article
Database	Repository for Life Sciences

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Article ; Online: Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio.

Thiam, Patrick / Kloth, Christopher / Blaich, Daniel / Liebold, Andreas / Beer, Meinrad / Kestler, Hans A

Scientific reports

2024 Volume 14, Issue 1, Page(s) 5695

Abstract: The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box characteristic of most optimized models and the ... ...

Abstract	The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box characteristic of most optimized models and the undetermined generalization ability of the trained architectures. The current work tackles both issues in the radiology domain by focusing on developing an effective and interpretable cardiomegaly detection architecture based on segmentation models. The architecture consists of two distinct neural networks performing the segmentation of both cardiac and thoracic areas of a radiograph. The respective segmentation outputs are subsequently used to estimate the cardiothoracic ratio, and the corresponding radiograph is classified as a case of cardiomegaly based on a given threshold. Due to the scarcity of pixel-level labeled chest radiographs, both segmentation models are optimized in a semi-supervised manner. This results in a significant reduction in the costs of manual annotation. The resulting segmentation outputs significantly improve the interpretability of the architecture's final classification results. The generalization ability of the architecture is assessed in a cross-domain setting. The assessment shows the effectiveness of the semi-supervised optimization of the segmentation models and the robustness of the ensuing classification architecture.
MeSH term(s)	Humans ; Artificial Intelligence ; Cardiomegaly/diagnostic imaging ; Generalization, Psychological ; Heart ; Image Processing, Computer-Assisted ; Neural Networks, Computer
Language	English
Publishing date	2024-03-08
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-024-56079-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: GatekeepR: an R Shiny application for the identification of nodes with high dynamic impact in Boolean networks.

Weidner, Felix M / Ikonomi, Nensi / Werle, Silke D / Schwab, Julian D / Kestler, Hans A

Bioinformatics (Oxford, England)

2024 Volume 40, Issue 1

Abstract: Motivation: Boolean networks can serve as straightforward models for understanding processes such as gene regulation, and employing logical rules. These rules can either be derived from existing literature or by data-driven approaches. However, in the ... ...

Abstract	Motivation: Boolean networks can serve as straightforward models for understanding processes such as gene regulation, and employing logical rules. These rules can either be derived from existing literature or by data-driven approaches. However, in the context of large networks, the exhaustive search for intervention targets becomes challenging due to the exponential expansion of a Boolean network's state space and the multitude of potential target candidates, along with their various combinations. Instead, we can employ the logical rules and resultant interaction graph as a means to identify targets of specific interest within larger-scale models. This approach not only facilitates the screening process but also serves as a preliminary filtering step, enabling the focused investigation of candidates that hold promise for more profound dynamic analysis. However, applying this method requires a working knowledge of R, thus restricting the range of potential users. We, therefore, aim to provide an application that makes this method accessible to a broader scientific community. Results: Here, we introduce GatekeepR, a graphical, web-based R Shiny application that enables scientists to screen Boolean network models for possible intervention targets whose perturbation is likely to have a large impact on the system's dynamics. This application does not require a local installation or knowledge of R and provides the suggested targets along with additional network information and visualizations in an intuitive, easy-to-use manner. The Supplementary Material describes the underlying method for identifying these nodes along with an example application in a network modeling pancreatic cancer. Availability and implementation: https://www.github.com/sysbio-bioinf/GatekeepR https://abel.informatik.uni-ulm.de/shiny/GatekeepR/.
MeSH term(s)	Gene Regulatory Networks ; Software ; Gene Expression Regulation
Language	English
Publishing date	2024-01-09
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btae007
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Article ; Online: A protocol for the use of cloud-based quantum computers for logical network analysis of biological systems.

Weidner, Felix M / Rossini, Mirko / Ankerhold, Joachim / Kestler, Hans A

STAR protocols

2023 Volume 4, Issue 3, Page(s) 102438

Abstract: Boolean networks are commonly used in systems biology to dynamically model gene regulatory interactions. Here, we present a protocol for implementing Boolean network dynamics as quantum circuits. We describe steps for accessing cloud-based quantum ... ...

Abstract	Boolean networks are commonly used in systems biology to dynamically model gene regulatory interactions. Here, we present a protocol for implementing Boolean network dynamics as quantum circuits. We describe steps for accessing cloud-based quantum processing units offered by IBM and IonQ and downloading and parsing logic for gene regulatory networks. We then detail procedures for performing simulations of quantum circuits on local devices and visualizing measurement results. For complete details on the use and execution of this protocol, please refer to Weidner et al.
MeSH term(s)	Cloud Computing ; Computers ; Systems Biology ; Logic ; Gene Regulatory Networks
Language	English
Publishing date	2023-08-06
Publishing country	United States
Document type	Journal Article
ISSN	2666-1667
ISSN (online)	2666-1667
DOI	10.1016/j.xpro.2023.102438
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Article ; Online: AMBAR - Interactive Alteration annotations for molecular tumor boards.

Fürstberger, Axel / Ikonomi, Nensi / Kestler, Angelika M R / Marienfeld, Ralf / Schwab, Julian D / Kuhn, Peter / Seufferlein, Thomas / Kestler, Hans A

Computer methods and programs in biomedicine

2023 Volume 240, Page(s) 107697

Abstract: ... AMBAR is dockerized, open source and available at https://sysbio.uni-ulm.de/?Software:Ambar Contact:hans ... kestler@uni-ulm.de. ...

Abstract	Motivation: Personalized decision-making for cancer therapy relies on molecular profiling from sequencing data in combination with database evidence and expert knowledge. Molecular tumor boards (MTBs) bring together clinicians and scientists with diverse expertise and are increasingly established in the clinical routine for therapeutic interventions. However, the analysis and documentation of patients data are still time-consuming and difficult to manage for MTBs, especially as few tools are available for the amount of information required. Results: To overcome these limitations, we developed an interactive web application AMBAR (Alteration annotations for Molecular tumor BoARds), for therapeutic decision-making support in MTBs. AMBAR is an R shiny-based application that allows customization, interactive filtering, visualization, adding expert knowledge, and export to clinical systems of annotated mutations. Availability: AMBAR is dockerized, open source and available at https://sysbio.uni-ulm.de/?Software:Ambar Contact:hans.kestler@uni-ulm.de.
MeSH term(s)	Humans ; Neoplasms/genetics ; Software
Language	English
Publishing date	2023-07-06
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	632564-6
ISSN	1872-7565 ; 0169-2607
ISSN (online)	1872-7565
ISSN	0169-2607
DOI	10.1016/j.cmpb.2023.107697
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Article ; Online: A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective.

Werle, Silke D / Ikonomi, Nensi / Lausser, Ludwig / Kestler, Annika M T U / Weidner, Felix M / Schwab, Julian D / Maier, Julia / Buchholz, Malte / Gress, Thomas M / Kestler, Angelika M R / Kestler, Hans A

NPJ systems biology and applications

2023 Volume 9, Issue 1, Page(s) 22

Abstract: Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific ... ...

Abstract	Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific biomarkers are missing. Moreover, the heterogeneity of PanNETs makes their treatment challenging and most approved targeted therapeutic options for PanNETs lack objective responses. Here, we applied a systems biology approach integrating dynamic modeling strategies, foreign classifier tailored approaches, and patient expression profiles to predict PanNETs progression as well as resistance mechanisms to clinically approved treatments such as the mammalian target of rapamycin complex 1 (mTORC1) inhibitors. We set up a model able to represent frequently reported PanNETs drivers in patient cohorts, such as Menin-1 (MEN1), Death domain associated protein (DAXX), Tuberous Sclerosis (TSC), as well as wild-type tumors. Model-based simulations suggested drivers of cancer progression as both first and second hits after MEN1 loss. In addition, we could predict the benefit of mTORC1 inhibitors on differentially mutated cohorts and hypothesize resistance mechanisms. Our approach sheds light on a more personalized prediction and treatment of PanNET mutant phenotypes.
MeSH term(s)	Humans ; Neuroendocrine Tumors/genetics ; Neuroendocrine Tumors/therapy ; Neuroendocrine Tumors/metabolism ; Nuclear Proteins/genetics ; Pancreatic Neoplasms/genetics ; Pancreatic Neoplasms/therapy ; Pancreatic Neoplasms/metabolism ; Systems Biology ; Phenotype ; Mechanistic Target of Rapamycin Complex 1/genetics
Chemical Substances	Nuclear Proteins ; Mechanistic Target of Rapamycin Complex 1 (EC 2.7.11.1)
Language	English
Publishing date	2023-06-03
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2056-7189
ISSN (online)	2056-7189
DOI	10.1038/s41540-023-00283-8
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Article ; Online: Discrete Logic Modeling of Cell Signaling Pathways.

Ikonomi, Nensi / Werle, Silke D / Schwab, Julian D / Kestler, Hans A

Methods in molecular biology (Clifton, N.J.)

2022 Volume 2488, Page(s) 159–181

Abstract: Cell signaling pathways often crosstalk generating complex biological behaviors observed in different cellular contexts. Frequently, laboratory experiments focus on a few putative regulators, alone unable to predict the molecular mechanisms behind the ... ...

Abstract	Cell signaling pathways often crosstalk generating complex biological behaviors observed in different cellular contexts. Frequently, laboratory experiments focus on a few putative regulators, alone unable to predict the molecular mechanisms behind the observed phenotypes. Here, systems biology complements these approaches by giving a holistic picture to complex signaling crosstalk. In particular, Boolean network models are a meaningful tool to study large network behaviors and can cope with incomplete kinetic information. By introducing a model describing pathways involved in hematopoietic stem cell maintenance, we present a general approach on how to model cell signaling pathways with Boolean network models.
MeSH term(s)	Kinetics ; Logic ; Models, Biological ; Signal Transduction ; Systems Biology
Language	English
Publishing date	2022-03-26
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-2277-3_12
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