Search NCBI databases (original) (raw)
Literature
Literature databases
Ontology used for PubMed indexing
Books, journals and more in the NLM Collections
Scientific and medical abstracts/citations
Data
Genes
Gene sequences and annotations used as references for the study of orthologs structure, expression, and evolution
Collected information about gene loci
Gene expression and molecular abundance profiles
Sequence sets from phylogenetic and population studies
Proteins
Protein sequences, 3-D structures, and tools for the study of functional protein domains and active sites
Experimentally-determined biomolecular structures
BLAST
A tool to find regions of similarity between biological sequences
Search nucleotide sequence databases
Search protein sequence databases
Search protein databases using a translated nucleotide query
Search translated nucleotide databases using a protein query
Genomes
Genome sequence assemblies, large-scale functional genomics data, and source biological samples
Biological projects providing data to NCBI
Descriptions of biological source materials
Genome sequencing projects by organism
High-throughput sequence reads
Taxonomic classification and nomenclature
Clinical
Heritable DNA variations, associations with human pathologies, and clinical diagnostics and treatments
Privately and publicly funded clinical studies conducted around the world
Human variations of clinical significance
Genotype/phenotype interaction studies
Short genetic variations
Genome structural variation studies
Genetic testing registry
Medical genetics literature and links
Online mendelian inheritance in man
PubChem
Repository of chemical information, molecular pathways, and tools for bioactivity screening
Chemical information with structures, information and links
Molecular pathways with links to genes, proteins and chemicals
Deposited substance and chemical information
News
Recent blog posts
NIH Director's Blog OCT. 8, 2024
NIH’s CARE for Health Primary Care Research Network: Connecting the Lab, the Clinic, and the Community
Since I became NIH Director last year, one key principle has guided my vision and approach: Our work is not finished when we deliver scientific discoveries; our work is finished when all people are living long and healthy lives. But unfortunately, we’re seeing some alarming trends in the health of the U.S. population. It’s a bit of a puzzle. On one hand, significant advances in biomedical research over the last several decades have led to lifesaving interventions for a range of diseases and conditions. At the same time, the overall health of the people in this country appears to be stalled and even getting worse.
NIH Director's Blog OCT. 3, 2024
AI Model Takes New Approach to Performing Diagnostic Tasks in Multiple Cancer Types
In recent years, medical researchers have been looking for ways to use artificial intelligence (AI) technology for diagnosing cancer. So far, most AI models have been developed to perform specific tasks in cancer diagnosis, such as detecting cancer presence or predicting a tumor’s genetic profile in certain cancer types. But what if an AI system could be more flexible, like a large language model such as ChatGPT, performing a variety of diagnostic tasks across multiple cancer types? As reported in the journal Nature, researchers have developed an AI system that can perform a wide range of cancer evaluation tasks and outperforms current AI methods in tasks like cancer cell detection and tumor origin identification. It was tested on 19 cancer types, leading the researchers to refer to it as “ChatGPT-like” in its flexibility. According to the research team, whose work is supported in part by NIH, this is also the first AI model based on analyzing slide images to not only accurately predict if a cancer is likely to respond to treatment, but also to validate these predictions across multiple patient groups around the world.