Analytics for Life Sciences

AI & Cloud Software Suite and SaaS enabled Platform for AI and Analytics Team to focus on Life Sciences Data Management, Annotation Automation, Model Management, MLOps Automation and Life Sciences data security

Solutions / glosys Analytics / Life Sciences

glosys Life Sciences AI Overview

glosys Life Sciences AI, One of the components of glosys AI Platform, provides AI & Cloud Software Suite and SaaS Applications and Services for AI and Analytics Team to focus on Life Sciences Data Management, Annotation Automation, Model Management, MLOps Automation and Life Sciences data security in the digital world

Features We offer

Life Sciences Data Management

glosys Life Sciences AI manages Life Sciences data sets in terms of data extraction, transformation, loading and processing effectively

Life Sciences Annotation Automation

glosys Life Sciences AI focuses on auto-annotating, Life Sciences image and video annotations, interpolate and fine tune the performance of the annotator for Life Sciences data


Life Sciences Models Management

glosys Life Sciences AI leverages construction of Life Sciences ML Pipelines, Auto-ML to develop production-ready Life Sciences AI, Model Workflows, Models Hub and Model Metrics for Life Sciences data

Life Sciences MLOps Automation

glosys Life Sciences AI harnesses the power of construction of Life Sciences CI/CD AI Pipelines using built-in neural networks, python SDK, webhooks and advanced orchestration

Life Sciences Data Security

glosys Life Sciences AI protects and secures image and video data using security features such as roles management, profiles and permissions management, access control and field level security

Model Types glosys Life Sciences AI leverages

Object Detection & Localization

Detect and locate the presence of multiple objects within an image, drawing bounding boxes around them to indicate their position and size

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Object Classification

Identify and assign a label or multiple labels to images based on the presence or absence of specific features or patterns within the image

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Captioning & Action Recognition

Automated process of generating textual description of an image, identify and classify human actions or movements within a video using action recognition

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Semantic Segmentation

Divide an image into distinct regions or segments, and assign labels representing the category of objects or features they belong to, to each individual pixel

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Instance Segmentation

Detect and delineate individual object instances within an image, and assign a unique label to each pixel that belongs to that instance

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Object Tracking

Follow or track the movement of one or more objects within a video sequence by detecting and matching features across frames.

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Usecases for Life Sciences

Biological Data Analysis

Analysis of biological data from various sources such as DNA sequences, protein structures, gene expression profiles, and metabolic pathways.

Genetic Sequence Analysis

Examining genetic sequences such as DNA, RNA, protein to identify patterns, variations.
Focus on sequence alignment, searching for homologous sequences, and predicting protein structures.
Identifying genes, regulatory elements, and functional elements within genomes for predicting gene locations, coding regions, promoters, and other genetic features.


Gene Expression

During gene expression, genetic codes from the DNA code are converted into a protein with the help of translation and transcription.
Regulation of gene expression includes different mechanisms through which our cells manage the amount of produced protein by our genes.
Functional genomics experiments are ranging from real-time PCR to high-throughput technologies such as microarrays and next generation sequencing

Drug Discovery and Bio-marker

To systematically build and score associations between drug targets and diseases.
Analyzing the three-dimensional structures of biomolecules such as proteins, nucleic acids using computational modeling and simulation techniques. Focuses on understanding their functions, interactions, and drug binding sites.
Leverages on Virtual Screening to analyze large databases of molecular structures to predict and prioritize molecules that are likely to interact with a target such as a protein involved in a disease and exhibit desired biological activity. This helps narrow down the pool of compounds for further investigation.
Significance on Chemoinformatics to predict molecular properties, such as solubility, toxicity, and bioavailability, which are crucial factors in determining a compound's suitability as a drug candidate. These predictions aid in selecting compounds with desirable characteristics.
Deals with Target Identification and Validation to identify potential drug targets by analyzing biological data, such as genetic information, protein interactions, and disease pathways. They assist in validating these targets by predicting their relevance and potential impact on disease mechanisms.
Understanding on De Novo Drug Design, Prediction of Drug-Target Interactions, Clinical Trial Optimization, Drug Repurposing and Adverse Effects Prediction

Pharmacogenomics for managed care

Focuses on Personalized Medicine as Pharmacogenomics allows for the customization of drug treatment based on an individual's genetic profile.

Multi-omics for Therapies

Multi-omics analyzes genomic, proteomic, epigenomic, phenomic, and omics data of patients to improve wellness and health outcomes through genome sequencing and analysis services for identification of new targets, and biomarkers associated with personalized therapies

Meet Your AI for Life Sciences Objectives & Needs