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12ANDDigest: A web tool for finding information in scientific publications and patents in the biological field
T. V. Ivanisenko1,2, P. S. Demenkov1,2, V. A. Ivanisenko1,2
1Institute of Cytology and Genetics SB RAS
2Kurchatov Genomics Center, Institute of Cytology & Genetics SB RAS
Email: itv@bionet.nsc.ru
DOI 10.24412/cl-35065-2021-1-02-45
We propose the ANDDigest tool [1], which is a new module of ANDSystem [2], dedicated to the search of
relevant scientific literature in the field of biology, considering many types of objects from the ANDSystem�s
ontology as well as sets of keywords, provided by the user. In contrast to the previous version of ANDDigest, a
proposed tool allows performing search not only in the sets of PubMed abstract, but also in patents, full-text
publications, and texts of pre-prints. The user has possibility to select one or several sources of the infor-
mation. Another approvement of the system is addition of the possibility to perform more complex searches.
The system has a user-friendly interface, providing sorting, visualization, and filtering of the found information,
including mapping of mentioned objects in text, linking to external databases, sorting of data by publication
date, citations number, J. H- indices, etc. The system provides data on trends for identified entities based
on dynamics of interest according to the frequency of their mentions in PubMed by years. The tool can be
applied to the interpretation of experimental genetics data, the search for associations between molecular
genetics objects, and the preparation of scientific and analytical reviews. It is presently available at
https://anddigest.sysbio.ru/.
This work was supported by the Kurchatov Genomics Center of the Institute of Cytology & Genetics SB RAS (project
number � 075-15-2019-1662).
References
1. Ivanisenko T. V., Saik O. V., Demenkov P. S., Ivanisenko N. V., Savostianov A. N., Ivanisenko V. A. ANDDigest: a new
web-based module of ANDSystem for the search of knowledge in the scientific literature // BMC bioinformatics. 2020.
V. 21, N. 11. P. 1-21.
2. Ivanisenko V. A., Saik O. V., Ivanisenko N. V., Tiys E. S., Ivanisenko T. V., Demenkov P. S., Kolchanov N. A.
ANDSystem: an Associative Network Discovery System for automated literature mining in the field of biology // BMC
systems biology. 2015. V. 9 (2), P. 1-10.
Reconstruction of associative gene networks using text mining methods
V. A. Ivanisenko1,2, E. A. Oshchepkova1, T. V. Ivanisenko1,2, P. S. Demenkov1,2
1Institute of Cytology and Genetics SB RAS
2Kurchatov Genomics Center, Institute of Cytology & Genetics SB RAS
Email: salix@bionet.nsc.ru
DOI 10.24412/cl-35065-2021-1-02-46
The ANDSystem software [1] was developed for the purpose of scanning literature for extracting relation-
ships between diseases, pathways, proteins, genes, microRNAs and metabolites and reconstruction of associa-
tive gene networks on the base of this information. The ANDSystem incorporates utilities for automated ex-
traction of knowledge from Pubmed published scientific texts and analysis of factographic databases. The
ANDVisio [2] is provided with various tools supporting filtering by object types, relationships between objects
and information sources; graph layout; search of the shortest pathway; cycles in graphs. An associative gene
network is a heterogeneous network, the vertices of which, along with molecular genetic objects (genes, pro-
teins, metabolites, etc.), can represent entities of a higher level (biological processes, diseases, environmental
factors, etc.) connected with each other by regulatory, physicochemical or associative interactions. A new di-
rection for the study of molecular genetic mechanisms is the prioritization of biological processes based on the
analysis of associative gene networks. Methods for prioritizing or ranking candidate genes according to their
importance in accordance with specified criteria based on the analysis of gene networks are widely used in
biomedicine to search for associations of genes with diseases, predict biomarkers, pharmacological targets,
etc. At the same time, there is a tendency to use them in other areas of knowledge, in particular in crop pro-
duction. This is largely due to the development of technologies for solving the problems of marker-oriented
and genomic selection, which require knowledge of the molecular genetic mechanisms underlying the for-
mation of economically valuable traits. Using ANDVisio, biological processes were prioritized according to the
degree of their connection with gene networks, presented in the ANDSystem knowledge base. With this ap-
proach it was analyzed a set of human diseases and the response of plants to cadmium, salt stress and drought
conditions.
This work was supported by the Kurchatov Genomics Center of the Institute of Cytology & Genetics SB RAS (project
No 075-15-2019-1662).
References
1. Ivanisenko V. A., Saik O. V., Ivanisenko N. V., Tiys E. S., Ivanisenko T. V., Demenkov P. S., Kolchanov N. A. ANDSys-
tem: an Associative Network Discovery System for automated literature mining in the field of biology // BMC systems
biology. 2015. V. 9 (2), P. 1-10.
2. Demenkov P. S., Ivanisenko, T. V., Kolchanov, N. A., Ivanisenko, V. A. ANDVisio: a new tool for graphic visualization
and analysis of literature mined associative gene networks in the ANDSystem // In silico biology. 2012. V. 11 (3, 4), P. 149-
161.
Algorithm for the study of the biomechanics of the shoulder joint in rehabilitation
E. M. Kabaev1, K. V. Simonov2, A. G. Zotin3, Yu. A. Hamad4, A. N. Matsulev2
1Federal Siberian Research Clinical Centre, Krasnoyarsk
2Institute of Computational Modelling SB RAS
3Reshetnev Siberian State University of Science and Technology, Krasnoyarsk
4Siberian Federal University, Krasnoyarsk
Email: kabaevem@mail.ru
DOI 10.24412/cl-35065-2021-1-02-47
The variability of anatomical and physiological features is often an additional risk factor for structural pa-
thologies and injuries of the shoulder joint. Studies of the kinematic patterns of the shoulder joint and the up-
per limb as a whole, as well as, their variability in norm and pathology are actively carried out in biomechanics,
rehabilitation, and sports medicine. Injuries to the structures of the shoulder joint are account for 16 to 55% of
all injuries of large joints [1, 2]. Clinical studies conducted in FSRCC FMBA in Krasnoyarsk. The objects of obser-
vation were men and women 18�55 years old in the early and late recovery periods after surgical treatment of
injuries of the shoulder joint [3]. The series of MRI images were studied using Shearlet transform and color-
coding algorithms [3, 4]. Demonstrated MRI images of patients with additional imaging. Improved the study of
joint morphology and geometry. The obtained data reflect the state of all components of the unified kinematic
model of the shoulder joint at a particular moment in the rehabilitation process. The proposed complex ap-
proach significantly improves the quality of the step-by-step diagnostics for injuries of the shoulder joint which
opens up prospects for its application in biomechanics and practical medicine. The dependencies in indicators
allow more accurately to plan the exercise cycle for a patient.
