Temat: discovery - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Soft computing tools for virtual drug discovery
Autorzy:: Hagan, D.
Hagan, M.
Powiązania:: https://bibliotekanauki.pl/articles/91628.pdf
Data publikacji:: 2018
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: drug discovery
virtual screening
multilayer network
SOM
Opis:: In this paper, we describe how several soft computing tools can be used to assist in high throughput screening of potential drug candidates. Individual small molecules (ligands) are assessed for their potential to bind to specific proteins (receptors). Committees of multilayer networks are used to classify protein-ligand complexes as good binders or bad binders, based on selected chemical descriptors. The novel aspects of this paper include the use of statistical analyses on the weights of single layer networks to select the appropriate descriptors, the use of Monte Carlo cross-validation to provide confidence measures of network performance (and also to identify problems in the data), the addition of new chemical descriptors to improve network accuracy, and the use of Self Organizing Maps to analyze the performance of the trained network and identify anomalies. We demonstrate the procedures on a large practical data set, and use them to discover a promising characteristic of the data. We also perform virtual screenings with the trained networks on a number of benchmark sets and analyze the results.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2018, 8, 3; 173-189
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: On knowledge discovery and representations of molecular structures using topological indices
Autorzy:: Alsaadi, Fawaz E.
Bokhary, Syed Ahtsham Ul Haq
Shah, Aqsa
Ali, Usman
Cao, Jinde
Alassafi, Madini Obad
Rehman, Masood Ur
Rahman, Jamshaid Ul
Powiązania:: https://bibliotekanauki.pl/articles/2031152.pdf
Data publikacji:: 2021
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: graph network
sheet
topological index
cheminformatics
knowledge discovery
Opis:: The main purpose of a topological index is to encode a chemical structure by a number. A topological index is a graph invariant, which decribes the topology of the graph and remains constant under a graph automorphism. Topological indices play a wide role in the study of QSAR (quantitative structure-activity relationship) and QSPR (quantitative structure-property relationship). Topological indices are implemented to judge the bioactivity of chemical compounds. In this article, we compute the ABC (atom-bond connectivity); ABC4 (fourth version of ABC), GA(geometric arithmetic) and GA5(fifth version of GA) indices of some networks sheet. These networks include: octonano window sheet; equilateral triangular tetra sheet; rectangular sheet; and rectangular tetra sheet networks.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 1; 21-32
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Rule based networks : an efficient and interpretable representation of computational models
Autorzy:: Liu, H.
Gegov, A.
Cocea, M.
Powiązania:: https://bibliotekanauki.pl/articles/91698.pdf
Data publikacji:: 2017
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: rule based networks
knowledge discovery
predictive modelling
rule representation
Opis:: Due to the vast and rapid increase in the size of data, data mining has been an increasingly important tool for the purpose of knowledge discovery to prevent the presence of rich data but poor knowledge. In this context, machine learning can be seen as a powerful approach to achieve intelligent data mining. In practice, machine learning is also an intelligent approach for predictive modelling. Rule learning methods, a special type of machine learning methods, can be used to build a rule based system as a special type of expert systems for both knowledge discovery and predictive modelling. A rule based system may be represented through different structures. The techniques for representing rules are known as rule representation, which is significant for knowledge discovery in relation to the interpretability of the model, as well as for predictive modelling with regard to efficiency in predicting unseen instances. This paper justifies the significance of rule representation and presents several existing representation techniques. Two types of novel networked topologies for rule representation are developed against existing techniques. This paper also includes complexity analysis of the networked topologies in order to show their advantages comparing with the existing techniques in terms of model interpretability and computational efficiency.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2017, 7, 2; 111-123
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Mosaic reasoning for discoveries
Autorzy:: Stilman, B.
Powiązania:: https://bibliotekanauki.pl/articles/91717.pdf
Data publikacji:: 2013
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: algorithm optimizing warfighting
Linguistic Geometry
LG
Algorithm of Discovery
DNA
mosaic
Opis:: We investigate structure of the Primary Language of the human brain as introduced by J. von Neumann in 1957. Two components have been investigated, the algorithm optimizing warfighting, Linguistic Geometry (LG), and the algorithm for inventing new algorithms, the Algorithm of Discovery. The latter is based on multiple thought experiments, which manifest themselves via mental visual streams (“mental movies”). There are Observation, Construction and Validation classes of streams. Several visual streams can run concurrently and exchange information between each other. The streams may initiate additional thought experiments, program them, and execute them in due course. The visual streams are focused employing the algorithm of “a child playing a construction set” that includes a visual model, a construction set, and the Ghost. Mosaic reasoning introduced in this paper is one of the major means to focusing visual streams in a desired direction. It uses analogy with an assembly of a picture of various colorful tiles, components of a construction set. In investigating role of mosaic reasoning in the Algorithm of Discovery, in this paper, I replay a series of four thought experiments related to the discovery of the structure of the molecule of DNA. Only the fourth experiment was successful. This series of experiments reveals how a sequence of failures eventually leads the Algorithm to a discovery. This series permits to expose the key components of the mosaic reasoning, tiles and aggregates, local and global matching rules, and unstructured environment. In particular, it reveals the aggregates and the rules that played critical role in the discovery of the structure of DNA. They include the generator and the plug-in aggregates, the transformation and complementarity matching rules, and the type of unstructured environment. For the first time, the Algorithm of Discovery has been applied to replaying discoveries not related to LG and even to mathematics.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2013, 3, 3; 147-173
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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