Instance maps as an organising concept for complex experimental workflows as demonstrated for (nano)material safety research

• Benjamin Punz,
• Maja Brajnik,
• Joh Dokler,
• Jaleesia D. Amos,
• Litty Johnson,
• Katie Reilly,
• Anastasios G. Papadiamantis,
• Amaia Green Etxabe,
• Lee Walker,
• Diego S. T. Martinez,
• Steffi Friedrichs,
• Klaus M. Weltring,
• Nazende Günday-Türeli,
• Claus Svendsen,
• Christine Ogilvie Hendren,
• Mark R. Wiesner,
• Martin Himly,
• Iseult Lynch and
• Thomas E. Exner

Beilstein J. Nanotechnol. 2025, 16, 57–77, doi:10.3762/bjnano.16.7

• adapt to the nature of the data they were required to store. One innovative approach, taken by the NanoInformatics Knowledge Commons (NIKC) database [27], was to introduce the concept of the “nanomaterial instance” to capture the transformations that nanoscaled materials undergo in environmental and

The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential

• Dimitra-Danai Varsou,
• Arkaprava Banerjee,
• Joyita Roy,
• Kunal Roy,
• Giannis Savvas,
• Haralambos Sarimveis,
• Ewelina Wyrzykowska,
• Mateusz Balicki,
• Tomasz Puzyn,
• Georgia Melagraki,
• Iseult Lynch and
• Antreas Afantitis

Beilstein J. Nanotechnol. 2024, 15, 1536–1553, doi:10.3762/bjnano.15.121

• propose this approach as a valuable method for increasing the validity of nanoinformatics models and driving regulatory acceptance of in silico new approach methodologies for the use within an “Integrated Approach to Testing and Assessment” (IATA) for risk assessment of NMs. Keywords: consensus modelling

• effects. The integration of in silico new approach methodologies (NAMs) within the area of nanotechnology has created a plethora of possibilities for the assessment of NM properties and toxicity to support and/or substitute traditional experimental methodologies [2][3]. The field of nanoinformatics covers

• of nanoinformatics, various consensus approaches have been proposed over the past years for the prediction of different NM endpoints, such as NMs’ cellular uptake [20], zeta potential (ZP) [16], and electrophoretic mobility [21]. The complexity of predictive models requires the development of

Integrating high-performance computing, machine learning, data management workflows, and infrastructures for multiscale simulations and nanomaterials technologies

• Fabio Le Piane,
• Mario Vozza,
• Matteo Baldoni and
• Francesco Mercuri

Beilstein J. Nanotechnol. 2024, 15, 1498–1521, doi:10.3762/bjnano.15.119

• calculation of molecular descriptors that can be integrated into ML models [70]. Enalos NanoInformatics Cloud Platform is a web-based platform that allows users to design and build nanomaterials. It supports the calculation of molecular descriptors and the integration of these descriptors into ML models for

Interaction of graphene oxide with tannic acid: computational modeling and toxicity mitigation in C. elegans

• Romana Petry,
• James M. de Almeida,
• Francine Côa,
• Felipe Crasto de Lima,
• Diego Stéfani T. Martinez and
• Adalberto Fazzio

Beilstein J. Nanotechnol. 2024, 15, 1297–1311, doi:10.3762/bjnano.15.105

• /02317-2), Brazilian national institutes (INCT-Materials Informatics, INCT-Nanocarbono, INCT-Inomat and INCT-NanoAgro) and CompSafeNano-Brazil Project – Nanoinformatics approaches for safety and regulation of nanomaterials (CNPq Proc. No. 443735/2023-9). Conflict of Interest There are no conflicts to

Nanoinformatics for environmental health and biomedicine

• Rong Liu and
• Yoram Cohen

Beilstein J. Nanotechnol. 2015, 6, 2449–2451, doi:10.3762/bjnano.6.253

• Engineering Department, Los Angeles, California 90095, United States 10.3762/bjnano.6.253 Keywords: nanoinformatics; Nanotechnology has become a significant enabling technology for a wide array of industries being integrated across diverse areas such as medicine, electronics, biomaterials, and energy

• with nanotechnology processes and materials (i.e., “nano-data”). In order to address these requirements, nanoinformatics has emerged over the last decade as “The science and practice of determining which information is relevant to the nanoscale science and engineering community, and then developing and

• implementing effective mechanisms for collecting, validating, storing, sharing, analyzing, modeling, and applying that information.” [1]. At present, nanoinformatics focuses primarily on: nano-data management and database development, nano-data curation, assessment of the value of information in nano-data

An ISA-TAB-Nano based data collection framework to support data-driven modelling of nanotoxicology

• Richard L. Marchese Robinson,
• Mark T. D. Cronin,
• Andrea-Nicole Richarz and
• Robert Rallo

Beilstein J. Nanotechnol. 2015, 6, 1978–1999, doi:10.3762/bjnano.6.202

• business rules that extend the generic ISA-TAB-Nano specification as well as Python code to facilitate parsing and integration of these datasets within other nanoinformatics resources. The use of these resources is illustrated by a “Toy Dataset” presented in the Supporting Information. The strengths and

• weaknesses of the resources are discussed along with possible future developments. Keywords: databases; ISA-TAB-Nano; nanoinformatics; nanotoxicology; quantitative structure–activity relationship (QSAR); Introduction Nanotechnology, which may be considered the design and application of engineered

• anticipated that these resources will be of value for the research community. These resources were developed within the context of the NanoPUZZLES project [33], but their development was informed via discussions with various researchers in the nanoinformatics/nanotoxicology community and consideration of

Framework for automatic information extraction from research papers on nanocrystal devices

• Thaer M. Dieb,
• Masaharu Yoshioka,
• Shinjiro Hara and
• Marcus C. Newton

Beilstein J. Nanotechnol. 2015, 6, 1872–1882, doi:10.3762/bjnano.6.190

• on these results, we discuss future research plans for improving the performance of the system. Keywords: annotated corpus; automatic information extraction; nanocrystal device development; nanoinformatics; text mining; Introduction Nanoscale research is a rapidly progressing domain and many

• research papers containing experimental results have been published. Because it is a very time-consuming task to read through all related papers, several research efforts have been conducted in the nanoinformatics research domain. This includes the construction of databases for sharing the experimental

• variety of methods for the extraction of information from research papers [15][16][17]. In the nanoinformatics domain, only a few researchers have attempted to automatically extract information from research papers [18][19][20] and their frameworks are explicitly focused on nanomedicine applications

Nanocuration workflows: Establishing best practices for identifying, inputting, and sharing data to inform decisions on nanomaterials

• Christina M. Powers,
• Karmann A. Mills,
• Stephanie A. Morris,
• Fred Klaessig,
• Sharon Gaheen,
• Nastassja Lewinski and
• Christine Ogilvie Hendren

Beilstein J. Nanotechnol. 2015, 6, 1860–1871, doi:10.3762/bjnano.6.189

• nanoscience to compare and integrate information across diverse fields of study through informatics (i.e., nanoinformatics). This paper is one in a series of articles on the data curation process in nanoinformatics (nanocuration). Other articles in this series discuss key aspects of nanocuration (temporal

• groups) and providing nanocuration resources (e.g., training) will likely prove crucial for the wider application of nanocuration workflows in the scientific community. Keywords: curation; informatics; nanoinformatics; nanomaterials; workflows; Introduction A tremendous growth in resources and tools to

• (e.g., chemistry, toxicology, ecology, risk assessment, material science). The complexity of developing tools for accessing, sharing, and viewing data relevant to nanomaterials has generated an entire field known as nanoinformatics. This paper is one in a series and focuses on a particular aspect of

Nanotechnology in the real world: Redeveloping the nanomaterial consumer products inventory

• Marina E. Vance,
• Todd Kuiken,
• Eric P. Vejerano,
• Sean P. McGinnis,
• Michael F. Hochella Jr.,
• David Rejeski and
• Matthew S. Hull

Beilstein J. Nanotechnol. 2015, 6, 1769–1780, doi:10.3762/bjnano.6.181

• standardized methods and metrics for nanomaterial characterization and labelling in consumer products can lead to greater understanding between the key stakeholders in nanotechnology, especially consumers, researchers, regulators, and industry. Keywords: consumer products; database; inventory; nanoinformatics

• understand the transition of nanotechnology from the laboratory bench to the commercial marketplace substantiate the need for applying the concept of nanoinformatics to a nanotechnology-enabled consumer products database, which is to determine the most relevant and useful information needed by a variety of

The Nanomaterial Data Curation Initiative: A collaborative approach to assessing, evaluating, and advancing the state of the field

• Christine Ogilvie Hendren,
• Christina M. Powers,
• Mark D. Hoover and
• Stacey L. Harper

Beilstein J. Nanotechnol. 2015, 6, 1752–1762, doi:10.3762/bjnano.6.179

• these early stages of development, a single common aspect shared across all nanoinformatics resources is that data must be curated into them. Through exploration of sub-topics related to all activities necessary to enable, execute, and improve the curation process, the NDCI will provide a substantive

• analysis of nanomaterial data curation itself, as well as a platform for multiple other important discussions to advance the field of nanoinformatics. This article outlines the NDCI project and lays the foundation for a series of papers on nanomaterial data curation. The NDCI purpose is to: 1) present and

• the details of the interactive needs and workflows of data customers, data creators, and data analysts. Initial responses from stakeholder liaisons throughout the nanoinformatics community reveal a shared view that it will be critical to focus on integration of datasets with specific orientation

Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD) for brain cancer

• Ying Huang,
• Jing Ma,
• Alan L. Porter,
• Seokbeom Kwon and
• Donghua Zhu

Beilstein J. Nanotechnol. 2015, 6, 1666–1676, doi:10.3762/bjnano.6.169

• -enabled drug delivery (NEDD); nanoinformatics; Introduction Drug delivery research has grown rapidly over the past two decades and has enabled drug development by designing suitable delivery systems that improve efficacy, lower dosing frequency, and encourage patient convenience and compliance [1

Analysis of soil bacteria susceptibility to manufactured nanoparticles via data visualization

• Rong Liu,
• Yuan Ge,
• Patricia A. Holden and
• Yoram Cohen

Beilstein J. Nanotechnol. 2015, 6, 1635–1651, doi:10.3762/bjnano.6.166

• communities exposed to MNPs and thus evaluate the potential for environmental impacts. Keywords: environmental impact; manufactured nanoparticles; nanoinformatics; soil bacteria; visualization; Introduction Manufactured nanoparticles (MNPs) are now routinely used in numerous products and applications due to

The eNanoMapper database for nanomaterial safety information

• Nina Jeliazkova,
• Charalampos Chomenidis,
• Philip Doganis,
• Bengt Fadeel,
• Roland Grafström,
• Barry Hardy,
• Janna Hastings,
• Markus Hegi,
• Vedrin Jeliazkov,
• Nikolay Kochev,
• Pekka Kohonen,
• Cristian R. Munteanu,
• Haralambos Sarimveis,
• Bart Smeets,
• Pantelis Sopasakis,
• Georgia Tsiliki,
• David Vorgrimmler and
• Egon Willighagen

Beilstein J. Nanotechnol. 2015, 6, 1609–1634, doi:10.3762/bjnano.6.165

• interfaces and graphical summaries of the data, and how these resources facilitate the modelling of reproducible quantitative structure–activity relationships for nanomaterials (NanoQSAR). Keywords: database; EU NanoSafety Cluster; nanoinformatics; nanomaterials; nanomaterials ontology; NanoQSAR; safety

• generating activities, such as NanoMiner [9]. An extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases is presented in two recent publications [10][11]. Reviews of emerging databases and analysis tools in nanoinformatics

How decision analysis can further nanoinformatics

• Matthew E. Bates,
• Sabrina Larkin,
• Jeffrey M. Keisler and
• Igor Linkov

Beilstein J. Nanotechnol. 2015, 6, 1594–1600, doi:10.3762/bjnano.6.162

• regulatory agencies to process and use the data. The vision of nanoinformatics is to address this problem by identifying the information necessary to support specific decisions (a top-down approach) and collecting and visualizing these relevant data (a bottom-up approach). Current nanoinformatics efforts

• Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges. Keywords: decision analysis; nanoinformatics; policy; portfolio analysis; risk assessment; value of information; weight of evidence

• essential to future developments in nanomaterial research [2]. Nanoinformatics is defined as (a) “the science and practice of determining which information is relevant to the nanoscale science and engineering community”, and (b) “developing and implementing effective mechanisms for collecting, validating

Experiences in supporting the structured collection of cancer nanotechnology data using caNanoLab

• Stephanie A. Morris,
• Sharon Gaheen,
• Michal Lijowski,
• Mervi Heiskanen and
• Juli Klemm

Beilstein J. Nanotechnol. 2015, 6, 1580–1593, doi:10.3762/bjnano.6.161

• by journals, databases, and researchers as an accepted format for annotating data – a requirement called for by these groups [17]. Similarly, in order for the nanoinformatics field to grow, the relevance of nanotechnology data and associated information must be emphasized by the community. In

Using natural language processing techniques to inform research on nanotechnology

• Nastassja A. Lewinski and
• Bridget T. McInnes

Beilstein J. Nanotechnol. 2015, 6, 1439–1449, doi:10.3762/bjnano.6.149

• online repositories to broaden participation in nanoinformatics. Keywords: data mining; informatics; name entity recognition; nano-informatics; nanoparticles; nanotechnology; nanotoxicity; natural language processing; text mining; Introduction Nanotechnology may still be considered a relatively new

• lagged behind. As a consequence, unlike bioinformatic areas such as genomics or systems biology, nanoinformatics is still in its infancy. Nanoinformatics is defined as “the science and practice of determining which information is relevant to the nanoscale science and engineering community, and then

• developing and implementing effective mechanisms for collecting, validating, storing, sharing, analyzing, modeling, and applying that information” [4]. Applications of nanoinformatics include data integration and exchange (e.g., caNanoLab, GoodNanoGuide), nanoparticle characterization (e.g., caNanoLab

Simulation tool for assessing the release and environmental distribution of nanomaterials

• Haoyang Haven Liu,
• Muhammad Bilal,
• Anastasiya Lazareva,
• Arturo Keller and
• Yoram Cohen

Beilstein J. Nanotechnol. 2015, 6, 938–951, doi:10.3762/bjnano.6.97

• : engineered nanomaterials; environmental exposure assessment; life cycle assessment; nanoinformatics; web-based simulation tool; Introduction Engineered nanomaterials (ENMs) are reported to be utilized in more than 1,000 commercial products owing to their unique size-related beneficial properties [1][2][3][4