ProSNEx (Protein Structure Network Explorer) is a web service for construction and analysis of Protein Structure Networks (PSNs) alongside amino acid flexibility, sequence conservation and annotation features. ProSNEx constructs a PSN by adding nodes to represent residues and edges between these nodes using user-specified interaction distance cutoffs for either carbon-alpha, carbon-beta or atom-pair contact networks. Different types of weighted networks can also be constructed by using either (i) the residue-residue interaction energies in the format returned by gRINN, resulting in a Protein Energy Network (PEN); (ii) the dynamical cross correlations from a coarse-grained Normal Mode Analysis (NMA) of the protein structure; (iii) interaction strength. Upon construction of the network, common network metrics (such as node centralities) as well as shortest paths between nodes and k-cliques are calculated. Moreover, additional features of each residue in the form of conservation scores and mutation/natural variant information are included in the analysis. By this way, tool offers an enhanced and direct comparison of network-based residue metrics with other types of biological information. ProSNEx is free and open to all users without login requirement at http://prosnex-tool.com.

Intrinsically disordered proteins (IDPs)/regions do not have well-defined secondary and tertiary structures, however, they are functional and it is critical to gain a deep understanding of their residue packing. The shape distributions methodology, which is usually utilized in pattern recognition, clustering, and classification studies in computer science, may be adopted to study the residue packing of the proteins. In this study, shape distributions of the globular proteins and IDPs were obtained to shed light on the residue packing of their structures. The shape feature that was used is the sphericity of tetrahedra obtained by Delaunay Tessellation of points of Cα coordinates. Then the sphericity probability distributions were compared by using Principal Component Analysis. This computational structural study shows that the set of IDPs constitute a more diverse set than the set of globular proteins in terms of the geometrical properties of their network structures.

The main roles of botanic gardens are to undertake research, share information, and conserve plant biodiversity. Conservation can not only be thought of in terms of genetic resources, but also scientific knowledge and information about the plants. There are different methods of recording data about living material in botanic gardens, ranging from the simple recording of information in handwritten books, to the use of sophisticated computer software programmes. In the case of electronically recorded information this can involve, complex construction of query sentences, that a majority of botanic garden staff are unable to write as they are not computer programmers, nor do they usually have any expertise of computer systems. Although there are a few computer programs used to store information about plants in botanic gardens, Otobur™, is straight forward and easy to use with innovative features. Developed by us at the Nezahat Gökyiğit Botanik Bahçesi, it runs on a platform-independent online system and has an improved dashboard for real-time statistics as well as multi-language support. Its ‘just click’ query builder can readily create a detailed report and it can also send information by email to users. Example features include an estimated flowering calendar. Otobur™ is an easy-to-use, open-source web application offering opportunities for adding other optional features.

Over the past decade, great improvements have occurred in the field of biodiversity information technology. Data types such as geographic and phenological (e.g., blooming) characteristics of different specimens, which are used for the analysis of environmental issues, are steadily increasing on a large scale. Most herbaria and botanic gardens are involved in the digital compilations of such kinds of data to be able to transform them into meaningful results that can be used to tackle environmental problems (Leadlay and Greene 1998). These are usually in the form of high resolution images, along with tables displaying additional information about specimens, which are accessible over the internet. This study, will describe how we made an annual estimate of phenological data, constructing a flowering calendar of plants (Fig. 1) in the Nezahat Gökyiğit Botanik Bahçesi (NGBB), using Otobur (Loizeau et al. 2018). Otobur is a data management system developed under NGBB in Istanbul, which is accessible at https://www.otobur.org.tr. In addition to this, we also analyze our recorded data on the ongoing propagation effort of seedlings, in order to analyze and compare their prior germination success and mortality ratios (Fig. 2). This enables us to improve our procedures, and to find the most suitable techniques to apply in the most accurate propagation trials.