Alternative polyadenylation and dynamic 3' UTR length is associated with polysome recruitment throughout the cardiomyogenic differentiation of hESCs.

Alternative polyadenylation (APA) increases transcript diversity through the generation of isoforms with varying 3' untranslated region (3' UTR) lengths. As the 3' UTR harbors regulatory element target sites, such as miRNAs or RNA-binding proteins, changes in this region can impact post-transcriptional regulation and translation. Moreover, the APA landscape can change based on the cell type, cell state, or condition. Given that APA events can impact protein expression, investigating translational control is crucial for comprehending the overall cellular regulation process. Revisiting data from polysome profiling followed by RNA sequencing, we investigated the cardiomyogenic differentiation of pluripotent stem cells by identifying the transcripts that show dynamic 3' UTR lengthening or shortening, which are being actively recruited to ribosome complexes. Our findings indicate that dynamic 3' UTR lengthening is not exclusively associated with differential expression during cardiomyogenesis but rather with recruitment to polysomes. We confirm that the differentiated state of cardiomyocytes shows a preference for shorter 3' UTR in comparison to the pluripotent stage although preferences vary during the days of the differentiation process. The most distinct regulatory changes are seen in day 4 of differentiation, which is the mesoderm commitment time point of cardiomyogenesis. After identifying the miRNAs that would target specifically the alternative 3' UTR region of the isoforms, we constructed a gene regulatory network for the cardiomyogenesis process, in which genes related to the cell cycle were identified. Altogether, our work sheds light on the regulation and dynamic 3' UTR changes of polysome-recruited transcripts that take place during the cardiomyogenic differentiation of pluripotent stem cells.

A web-based platform for the annotation and analysis of NAR-published databases.

Biological databases are essential resources for life science research, but finding and selecting the most relevant and up-to-date databases can be challenging due to the large number and diversity of available databases. The Nucleic Acids Research (NAR) journal publishes annual database issues that provide a comprehensive list of databases in the molecular biology domain. However, the information provided by NAR is limited and sometimes does not reflect the current status and quality of the databases. In this article, we present a web-based platform for the annotation and analysis of NAR-published databases. The platform allows users to manually curate and enrich the NAR entries with additional information such as availability, downloadability, source code links, cross-references, and duplicates. Statistics and visualizations on various aspects of the database landscape, such as recency, status, category, and curation history are also provided. Currently, it contains a total of 2,246 database entries of which 2,025 are unique with the majority updated within the last five years. Around 75% of all databases are still available and more than half provide a download option. Cross references to Database Commons are available for 1,889 entries. The platform is freely available online at https://nardbstatus.kalis-amts.de and aims to help researchers in database selection and decision-making. It also provides insights into the current state and challenges of a subset of all databases in the life sciences.

Simulation of the Refractive Index Variation and Validation of the Form Deviation in Precisely Molded Chalcogenide Glass Lenses (IRG 26) Considering the Stress and Structure Relaxation.

Precise infrared (IR) optics are core elements of infrared cameras for thermal imaging and night vision applications and can be manufactured directly or using a replicative process. For instance, precision glass molding (PGM) is a replicative manufacturing method that meets the demand of producing precise and accurate glass optics in a cost-efficient manner. However, several iterations in the PGM process are applied to compensate the induced form deviation and the index drop after molding. The finite element method (FEM) is utilized to simulate the thermomechanical process, predicting the optical properties of molded chalcogenide lenses and thus preventing costly iterations. Prior to FEM modelling, self-developed glass characterization methods for the stress and structure relaxation of chalcogenide glass IRG 26 are implemented. Additionally, a ray-tracing method is developed in this work to calculate the optical path difference (OPD) based on the mesh structure results from the FEM simulation. The developed method is validated and conducted during the production of molded lenses.

The heterogeneous pharmacological medical biochemical network PharMeBINet.

Heterogeneous biomedical pharmacological databases are important for multiple fields in bioinformatics. Hetionet is a freely available database combining diverse entities and relationships from 29 public resources. Therefore, it is used as the basis for this project. 19 additional pharmacological medical and biological databases such as CTD, DrugBank, and ClinVar are parsed and integrated into Neo4j. Afterwards, the information is merged into the Hetionet structure. Different mapping methods are used such as external identification systems or name mapping. The resulting open-source Neo4j database PharMeBINet has 2,869,407 different nodes with 66 labels and 15,883,653 relationships with 208 edge types. It is a heterogeneous database containing interconnected information on ADRs, diseases, drugs, genes, gene variations, proteins, and more. Relationships between these entities represent drug-drug interactions or drug-causes-ADR relations, to name a few. It has much potential for developing further data analyses including machine learning applications. A web application for accessing the database is free to use for everyone and available at https://pharmebi.net . Additionally, the database is deposited on Zenodo at https://doi.org/10.5281/zenodo.6578218 .

BioDWH2: an automated graph-based data warehouse and mapping tool.

Data integration plays a vital role in scientific research. In biomedical research, the OMICS fields have shown the need for larger datasets, like proteomics, pharmacogenomics, and newer fields like foodomics. As research projects require multiple data sources, mapping between these sources becomes necessary. Utilized workflow systems and integration tools therefore need to process large amounts of heterogeneous data formats, check for data source updates, and find suitable mapping methods to cross-reference entities from different databases. This article presents BioDWH2, an open-source, graph-based data warehouse and mapping tool, capable of helping researchers with these issues. A workspace centered approach allows project-specific data source selections and Neo4j or GraphQL server tools enable quick access to the database for analysis. The BioDWH2 tools are available to the scientific community at https://github.com/BioDWH2.

JIB.tools 2.0 - A Bioinformatics Registry for Journal Published Tools with Interoperability to bio.tools.

JIB.tools 2.0 is a new approach to more closely embed the curation process in the publication process. This website hosts the tools, software applications, databases and workflow systems published in the Journal of Integrative Bioinformatics (JIB). As soon as a new tool-related publication is published in JIB, the tool is posted to JIB.tools and can afterwards be easily transferred to bio.tools, a large information repository of software tools, databases and services for bioinformatics and the life sciences. In this way, an easily-accessible list of tools is provided which were published in JIB a well as status information regarding the underlying service. With newer registries like bio.tools providing these information on a bigger scale, JIB.tools 2.0 closes the gap between journal publications and registry publication. (Reference: https://jib.tools).

History and Future of KALIS: Towards Computer-assisted Decision Making in Prescriptive Medicine.

With an increasing older population in Germany and the need for polypharmacy to treat multimorbid patients computer-assisted decision making on an individual level is increasingly important to reduce prescription errors and adverse drug reactions. While current systems focus on guidelines and prescribing information, molecular information is equally important for explanation and discovery of drug-related problems. Based on the existing KALIS system and newer projects like PIMBase, a new concept for the KALIS-2 system is presented. Improvements to the modularisation of components enable future extension and greater maintainability. Interoperability with available electronic health records standards and protocols allows the integration and communication with existing workflows for healthcare professionals. Finally, new visualisation modes empower the user to explore and analyze the patient situation in an individual patient subgraph. For offline use and dialogue between patient and general practitioner, the results can be printed out using a new reporting tool. The adherence to findings from previous decision support systems and reasons for their failed adoption is an important task in the development of KALIS-2.

Data-Driven Assessment of Potentially Inappropriate Medication in the Elderly.

Multimorbid patients taking polypharmacy represent a growing population at high risk for inappropriate prescribing. Various lists for identifying potentially inappropriate medication are spread across scientific journals and difficult to access. To address this ongoing need, a new database named PIMBase is developed which integrates these well-known lists and unifies their rating scales. The analysis of the pharmacovigilance data reveals the benefits of combining the lists. PIMBase is meant to be a web-based system and starting point for the data-driven assessment of polypharmacy to identify inappropriate medication and to improve the quality of prescribing. PIMBase is available at https://pimbase.kalis-amts.de.

GenCoNet - A Graph Database for the Analysis of Comorbidities by Gene Networks.

The prevalence of comorbid diseases poses a major health issue for millions of people worldwide and an enormous socio-economic burden for society. The molecular mechanisms for the development of comorbidities need to be investigated. For this purpose, a workflow system was developed to aggregate data on biomedical entities from heterogeneous data sources. The process of integrating and merging all data sources of the workflow system was implemented as a semi-automatic pipeline that provides the import, fusion, and analysis of the highly connected biomedical data in a Neo4j database GenCoNet. As a starting point, data on the common comorbid diseases essential hypertension and bronchial asthma was integrated. GenCoNet (https://genconet.kalis-amts.de) is a curated database that provides a better understanding of hereditary bases of comorbidities.