Patents by Inventor Naveen Sivadasan

Naveen Sivadasan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240403555
    Abstract: Comprehensive and high-quality disease dictionaries are invaluable resources for tasks such as building ontologies, automated relation extraction, text summarization, question answering etc. Such curated resources are useful to clinicians, researchers, and various Biomedical Natural Language Processing tasks. However, these are manually curated and are labor and time intensive, and additionally suffer from lower recall and coverage is also less. Present disclosure provides systems and methods for augmenting rare disease dictionaries, wherein the system retrieves (new) rare diseases terms from medical literature that are related to the given dictionary terms (seed terms) and recommends new terms (or NPs) in a ranked order. This method is useful for rare diseases dictionary augmentation as a significant fraction of the top recommendations are new synonym candidates for dictionary augmentation.
    Type: Application
    Filed: May 9, 2024
    Publication date: December 5, 2024
    Applicant: Tata Consultancy Services Limited
    Inventors: THOMAS JOSEPH, ADITYA RAMAKRISHNA RAO, RAJGOPAL SRINIVASAN, SUJATHA KOTTE, NAVEEN SIVADASAN, SAIPRADEEP GOVINDAKRISHNAN VANGALA
  • Publication number: 20240145037
    Abstract: This disclosure relates generally to identifying candidate genome sequences. Next generation sequencing (NGS) is a massively parallel sequencing technique for identifying candidate genome sequences. The current state-of-the-art techniques for identifying candidate genome sequences does not efficiently address the problem of distributing abundance values across several related strains that are present in the reference under the same species. The disclosed technique proposes a technique for identifying candidate genome sequences by estimating coverage. The disclosed technique includes a local search-based optimization to compute maximum likelihood-based estimates using constrains on coverage/cardinality thresholds for identifying candidate genome sequences.
    Type: Application
    Filed: September 20, 2023
    Publication date: May 2, 2024
    Applicant: Tata Consultancy Services Limited
    Inventors: VIDUSHI WALIA, SAIPRADEEP VANGALA GOVINDAKRISHNAN, NAVEEN SIVADASAN, RAJGOPAL SRINIVASAN
  • Patent number: 11915792
    Abstract: This disclosure relates generally to a method and a system for profiling of metagenome samples. Most state of-art techniques for metagenomic profiling use homology-based, curated database of identified marker sequences generated after complex and costly pre-processing. The disclosed method and system for profiling of metagenome samples are a non-homology based, a non-marker based and an alignment free strain level profiling tools for microbe profiling. The disclosure works with a several k-mer based indexing techniques for constructing a compact and comprehensive multi-level indexing, wherein the multi-level indexing includes a L1-Index and a L2-Index. The multi-level indexing is used for profiling metagenomics by abundance estimation, wherein the abundance estimation includes a relative abundance and an absolute abundance.
    Type: Grant
    Filed: May 5, 2022
    Date of Patent: February 27, 2024
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Vidushi Walia, Naveen Sivadasan, Rajgopal Srinivasan, Kota Krishna Priya
  • Publication number: 20220392565
    Abstract: This disclosure relates generally to a method and a system for profiling of metagenome samples. Most state of-art techniques for metagenomic profiling use homology-based, curated database of identified marker sequences generated after complex and costly pre-processing. The disclosed method and system for profiling of metagenome samples are a non-homology based, a non-marker based and an alignment free strain level profiling tools for microbe profiling. The disclosure works with a several k-mer based indexing techniques for constructing a compact and comprehensive multi-level indexing, wherein the multi-level indexing includes a L1-Index and a L2-Index. The multi-level indexing is used for profiling metagenomics by abundance estimation, wherein the abundance estimation includes a relative abundance and an absolute abundance.
    Type: Application
    Filed: May 5, 2022
    Publication date: December 8, 2022
    Applicant: Tata Consultancy Services Limited
    Inventors: Vidushi Walia, Naveen Sivadasan, Rajgopal Srinivasan, Kota Krishna Priya
  • Patent number: 11348693
    Abstract: This disclosure relates generally to method and system for graph convolution based gene prioritization on heterogeneous networks. The method includes obtaining a set of entities for human rare diseases from one or more sources containing rare diseases, genes, phenotypes for rare diseases and biological pathways and constructing an initial heterogeneous network using each of an entity from the set of entities. the initial heterogeneous network applying Graph Convolution-based Association Scoring (GCAS) to the initial heterogeneous network to derive inferred associations and creating a Heterogeneous Association Network for Rare Diseases (HANRD) by adding the inferred associations to the initial heterogeneous network and generating a prioritized set of genes for an input query being received in the HANRD.
    Type: Grant
    Filed: April 8, 2019
    Date of Patent: May 31, 2022
    Assignee: Tata Consultancy Services Limited
    Inventors: Thomas Joseph, Aditya Rao, Naveen Sivadasan, Saipradeep Govindakrishnan Vangala, Sujatha Kotte, Rajgopal Srinivasan
  • Publication number: 20220157401
    Abstract: There is a demand for low-cost efficient robust method for mapping read sequences with genome variation graph in genomic study. This disclosure herein relates to a method and system for mapping read sequences with genome variation graph by constructing a subgraph using a novel combination of graph embedding and graph winnowing techniques. The system processes the obtained plurality of read sequences and a genome variation graph for constructing the subgraph by computing an embedding for the genome variation graph utilizing a graph embedding technique. Further, graph index is generated for the genome variation graph based on the embedding and the genome variation graph utilizing the graph winnowing technique. Then computes gapped alignment score for read sequence (r) with its corresponding subgraph. Thus, enables a reliable method for read sequence with accurate, memory efficient and scalable system for mapping read sequences with genome variation graph.
    Type: Application
    Filed: March 13, 2020
    Publication date: May 19, 2022
    Applicant: Tata Consultancy Services Limited
    Inventors: Kavya Naga Sai VADDADI, Naveen SIVADASAN, Rajgopal SRINIVASAN
  • Publication number: 20210125690
    Abstract: Diagnosis of rare human diseases using DNA sequencing is a fast growing area of research. Conventional methods carries a risk of incorrect phenotype interpretation. However, obtaining a correct genotype and phenotype matching is challenging. A system for matching phenotype descriptions and pathogenic variants provides a one to one mapping of the phenotype and genotypes of a plurality of subjects under test. Initially, a plurality of phenotypes and a plurality of genome sequences are segmented based on metadata. A phenotype driven gene prioritization and a variant prioritization is applied on the segmented data method. A similarity score is calculated between the phenotype driven gene prioritization output and the variant prioritization output. The similarity score is further utilized to obtain a one to one matching of the plurality of phenotypes and the plurality of genotype sequences of the plurality of subjects under test.
    Type: Application
    Filed: September 21, 2020
    Publication date: April 29, 2021
    Applicant: Tata Consultancy Services Limited
    Inventors: Thomas Joseph, Aditya Ramkrishna Rao, Saipradeep Vangala Govindakrishnan, Naveen Sivadasan, Uma Sunderam, Sujatha Kotte, Rajgopal Srinivasan
  • Publication number: 20190311811
    Abstract: This disclosure relates generally to method and system for graph convolution based gene prioritization on heterogeneous networks. The method includes obtaining a set of entities for human rare diseases from one or more sources containing rare diseases, genes, phenotypes for rare diseases and biological pathways and constructing an initial heterogeneous network using each of an entity from the set of entities. the initial heterogeneous network applying Graph Convolution-based Association Scoring (GCAS) to the initial heterogeneous network to derive inferred associations and creating a Heterogeneous Association Network for Rare Diseases (HANRD) by adding the inferred associations to the initial heterogeneous network and generating a prioritized set of genes for an input query being received in the HANRD.
    Type: Application
    Filed: April 8, 2019
    Publication date: October 10, 2019
    Applicant: Tata Consultancy Services Limited
    Inventors: Thomas JOSEPH, Aditya RAO, Naveen SIVADASAN, Saipradeep Govindakrishnan VANGALA, Sujatha KOTTE, Rajgopal Srinivasan
  • Patent number: 10176188
    Abstract: Systems and methods for automated creation of a dictionary of scientific terms are described herein. Initially, input data is filtered to obtain a primary file having a plurality of term-ID pairs with each term-ID pair having a unique term ID and a scientific term. Further, a remove-term file is generated based on one or more term-ID pairs identified from the primary file such that the scientific terms of each term-ID pair corresponds to one of additional terms, frequent scientific terms, and undesirable terms. At least one term-ID pair from among the one or more term-ID pairs is altered to obtain a modified term-ID pair based on modification rules. The modified term-ID pair is added to an add-term file and a modified file is obtained based on the remove-term file and the add-term file. Duplicate term-ID pairs present in the modified file are removed to obtain the dictionary of scientific terms.
    Type: Grant
    Filed: January 29, 2013
    Date of Patent: January 8, 2019
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Rajgopal Srinivasan, Thomas Joseph, Venkat Raghavan Ganesh Sekar, Saipradeep Govindakrishnan Vangala, Naveen Sivadasan