Abstract: A system and a method for token-based classification for reducing overlap in field extraction during parsing of a text is disclosed. The method includes extracting text from a resource. The method further includes splitting one or more sentences into a predetermined number of plurality of tokens. The method furthermore includes generating a plurality of lists using a machine learning model for identifying one or more fields in the text. The plurality of lists comprises at least a list of tokens, a list of tags and a list of confidence scores of tokens. The method furthermore includes post processing the plurality of lists for extracting one or more fields for parsing the text.

Abstract: A method of generating an ontology for enhanced search is disclosed that includes an iterative process. The method includes loading seed entities in a memory and using a look-up API to search a first set of similar terms for each seed entity from a web-based database. The first set of similar terms is then clustered based on different concepts to obtain a first cluster of similar terms. The method further includes determining a second set of similar terms for each seed entity based on a category of each seed entity. The second set of similar terms is then clustered based on the different concepts to obtain a second cluster of similar terms. The first and second clusters are merged to generate the ontology of the seed entities. The iterative process is repeated until a saturation point is reached, at which point the generated ontology is considered complete.

Abstract: A system and a method for converting protein data bank (PDB) files into a grayscale image array is provided. The method includes extracting PDB files from a PDB, using a data extraction module. The method also includes converting, using a file conversion module, the PDB files into a data frame based on BioPandas. The method further includes selecting, using a column selection module, one or more columns from the data frame based on a pre-determined criteria. The method furthermore includes converting, using a column conversion module, the selected one or more columns into a NumPy array for rendering the data frame to resemble an image. The method furthermore includes resizing the NumPy array using an OpenCV for making size of the NumPy array uniform and for generating a grayscale image array.

Abstract: A system and a method for predicting a binding affinity of protein structures based on deep learning is disclosed. The method includes capturing, using a data capture module, a multi-dimensional structure of a plurality of protein-protein complexes from a protein sequence data set. The method also includes performing featurization, using a featurization module, of the multi-dimensional structure of the plurality of protein-protein complexes by creating an adjacency matrix for successive spherical shells centered around each type of a plurality of amino acid sequences. The method further includes predicting, using a prediction module, a binding affinity from text sequence of the plurality of amino acid sequences using a pre-trained artificial intelligence model based on the adjacency matrix.

Abstract: A system and a method for converting a protein data bank file into a two-dimensional numerical matrix is provided. The method also includes extracting PDB files from a PDB, using a data extraction module. The method further includes analyzing the PDB files using an analysis module for calculating and visualizing interatomic interactions in protein structures. The method further includes generating, using a file generation module, a comma separated values (CSV) file based on the analysis. The method further includes performing a featurization of the CSV file using a featurization module. The method further includes generating, using a matrix generating module, the two-dimensional numerical matrix based on the featurization.

Abstract: A method and system for generating a plurality of antibody sequences of a target from one or more framework regions based on at least one model. The model is trained on a training dataset of high binding affinity to generate the complementarity determining regions (CDR) from the received one or more framework regions (FR). The generated complementarity determining regions (CDR) from the each of the one or more framework regions (FR) are combined with the associated one or more framework regions to generate one or more regions of the target. The generated one or more regions comprises each of the received one or more framework regions (FR) and corresponding each of the generated complementarity determining regions (CDR). The generated one or more regions are concatenated to generate the plurality of antibody sequences of the target. The generated plurality of antibody sequences of the target has high binding affinity.

Abstract: A method and system for generating a plurality of new antibody sequences corresponding to a target from a single lead antibody sequence. A model is pre-trained with a training dataset of plurality of known antibody sequences to learn a structural pattern from the plurality of known antibody sequences. The method includes receiving the single lead antibody sequence. The lead antibody sequence has one or more regions. The regions have one or more lead framework regions (FR) and one or more lead complementarity determining regions (CDR). The pre-trained model is configured to process the single lead antibody sequence to identify a relationship between the one or more lead framework regions (FR) and one or more lead complementarity determining regions (CDR). A plurality of new antibody sequences are generated from the single lead antibody amino acid of the sequence by the pre-trained model based on the identified relationship and the structural pattern.

Abstract: The present invention provides a method and an apparatus for real-time remote sensing of a plurality of antenna configuration parameters in a radio access network (RAN) configured with the radio unit includes receiving the plurality of antenna configuration parameters by the sensor module from the antenna, transmitting the received plurality of antenna configuration parameters from the sensor module to a plurality of hardware devices using a programmable interface on the radio unit.

Abstract: Embodiments of the present disclosure relate to systems, methods, and user interfaces for monitoring and maintaining redundant network and storage paths. Initially, path check information is received at a path check server via one or more management nodes. Each of the one or more management nodes comprises one or more physical nodes corresponding to network and hardware infrastructure. Failed nodes of the one or more physical nodes are identified, the failed nodes indicating physical nodes having path failures. Upon determining the node does not have an active incident in progress, an incident corresponding to the node is generated. In embodiments, a notification may be communicated to one or more team members. The notification may include the incident and a status of the incident. In embodiments, data visualization corresponding to the incident may be provided.