# Troubleshooting NCBI Taxonomy Search: Why Your Organism Isn't Found When an NCBI taxonomy search comes back empty, the problem is usually the query string, not the database. The fastest check is to paste the plain scientific binomial with no abbreviations, no authority names in parentheses, and no strain suffix. Escherichia coli resolves immediately to its taxonomy identifier (taxid) 562. The abbreviation E. coli returns nothing. A large share of failed searches end at exactly that step. This article covers troubleshooting NCBI taxonomy search from the most common cause to the rarest. Each section explains the mechanism behind the failure and the fix. A troubleshooting table collects the symptoms in one place, a ten-step diagnostic sequence walks you from the obvious to the obscure, and a prevention section shows how to keep names and taxids from breaking your work later. These failures are not a beginner's problem. Working research groups build entire reviews on the Taxonomy Browser [1] and integrate NCBI records into phylogenomic datasets [2], and they hit the same walls. The eight causes below account for nearly all of them. ## Start Here: The Sixty-Second Check ![Decision path showing which part of a query to remove first, from abbreviation to authority string to strain suffix, ending in the plain binomial.](/article-images/illustrations/ncbi-taxonomy-search-not-working-sixty-second-check.webp) Run this checklist against your query before you troubleshoot anything deeper. 1. Expand every abbreviation. E. coli, S. aureus, and T. cacao fail as typed. The full binomials Escherichia coli, Staphylococcus aureus, and Theobroma cacao resolve. 2. Delete the authority string. A query like Escherichia coli (Migula 1895) breaks because Entrez, the unified retrieval system behind every NCBI database, treats the parenthetical authorship and year as extra search terms. 3. Delete strain, isolate, and cultivar suffixes. Strip a strain or cultivar label first, run the plain species, and add the suffix back only after the species resolves. 4. Spell out Greek letters. The database stores Betacoronavirus and Gammaproteobacteria, not β-coronavirus or γ-proteobacteria. 5. Remove accents and special characters. Type unaccented letters, replace the hybrid multiplication sign with the letter x, and drop apostrophes. 6. Check the spelling letter by letter. Staphylococus with one c returns nothing, and the search will not guess your intent. 7. Try the common name. human, mouse, dog, and cow all resolve. Obscure folk names do not. If the plain binomial still returns nothing, work through the causes below in order. ## How NCBI Taxonomy Stores Names Every organism in the database is a node with a unique taxid. The human node is taxid 9606, the mouse is 10090, and the fruit fly Drosophila melanogaster is 7227. Each node carries a scientific name, a rank (species, genus, family, and so on), a pointer to its parent node, a lineage (the full chain of ancestors up to the root of the tree), a list of synonyms (older or alternative names for the same organism), and any common names. The browser address for a node follows a stable pattern, so a link such as https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=9606 can be saved and shared. Three properties of the database explain most search failures. First, Taxonomy is built around names attached to sequence data in GenBank (NCBI's archive of submitted sequences), plus curated additions from the literature and partner sources. A name that has never been attached to a submitted sequence and has never been imported can be absent even though it was validly published in a journal. Second, the database keeps history. When a taxon is renamed, the old name usually survives as a synonym on the record, and most synonym searches resolve automatically. When two nodes are combined, the retired taxid is recorded as merged and redirects to the surviving node. Deleted nodes are logged too. The downloadable archive of the whole database, the taxdump, ships files named merged.dmp and delnodes.dmp that list exactly these events. Third, ranks below species are real and searchable, but readers often do not realize they are querying them. A taxonomy-guided review of Amaryllidaceae alkaloids worked through a family of more than 1,200 species organized into three subfamilies, with 58 genera inside the largest subfamily [1]. A search for a subgenus name only succeeds if you know the string belongs to a subgenus and is stored the way the database spells it. The Taxonomy Browser and the Entrez search box are two views of the same data. The browser shows one node at a time with its lineage. The search box queries all names at once. Both matter in troubleshooting, because a name that fails in one view sometimes reveals itself in the other. ## NCBI Taxonomy Search Not Working: Causes and Fixes at a Glance The table condenses the whole article. Symptom first, then the likely cause, the fastest way to confirm it, and the fix. | Symptom | Likely cause | How to confirm | Fix | |--|--|--|--| | A well-known species returns nothing | Abbreviation, authority string, or strain suffix in the query | Expand E. coli to Escherichia coli and delete (Migula 1895) | Search the plain binomial | | A species described this year returns nothing | The name is not in Taxonomy yet | Search the parent genus and scan the species list | Browse the parent taxon, BLAST a sequence, or wait for processing | | A strain, cultivar, or isolate returns nothing | Strain-level names live in BioSample, Assembly, and SRA, not Taxonomy | Run the same string in BioSample or Assembly | Resolve the species, then filter the sequence databases by strain | | The search returns an unrelated organism | The string matches a synonym or a homonym | Open the record and read the lineage and the Synonyms field | Combine the name with its parent genus using AND, or use the taxid | | An older name from the literature returns nothing | The name is a historical synonym or the node was merged | Search the current name and read the Synonyms field | Use the current taxid and record the synonym in your notes | | A wildcard search fails | The stem is shorter than four characters or the search exceeds 600 matches | Count the characters before the asterisk | Lengthen the stem or narrow the query with AND | | An E-utilities call errors or returns nothing | Unencoded spaces, a wrong db value, or rate limiting | Read the HTTP status code and the XML error text | Encode spaces, set db=taxonomy, add an API key, and slow the script down | | The name appears in PubMed but not in Taxonomy | The name exists only in the literature with no sequence record | Search the parent genus, then search Nucleotide for the string | Use the closest named parent taxon and request an addition through the Contact link | | An uncultured or metagenomic name returns nothing | Provisional labels like uncultured bacterium are not species entries | BLAST the 16S or ITS sequence against the targeted databases | Classify by sequence similarity and report the closest named taxon | | A virus name returns nothing | The virus is newly found or the classification name changed | Search the family or genus and browse its subgroups | Use the higher taxon and BLAST against the non-redundant databases | | The site loads but results look stale or broken | Browser cache or an extension interfering | Open the same search in a private window | Clear the cache, disable extensions, or use the wwwtax.cgi URL directly | The sections after the table explain each cause and the mechanism behind it. ## Cause 1: Formatting Problems in the Query Entrez reads a query as a set of terms with optional field tags. Anything extra changes the terms it searches. Abbreviations fail because the index stores full scientific names. E. coli is not a term in the index, so the search returns zero hits while the species sits at taxid 562 the whole time. Authority strings fail because the authorship and year become stray terms. The query Escherichia coli (Migula 1895) asks Entrez to match Migula and 1895 as well, and in the Taxonomy database that combination matches nothing. Greek letters fail because NCBI spells them out. Search Betacoronavirus, not β-coronavirus, and Gammaproteobacteria, not γ-proteobacteria. Accented characters fail because names are stored unaccented. Type the plain letter forms. In hybrid names, replace the multiplication sign with the letter x. Drop apostrophes and parentheses. If a name contains a hyphen, try it with and without the hyphen. Case is almost never the problem. Entrez is not case sensitive, so Escherichia coli and escherichia coli behave identically. Quotation marks deserve a note. In Entrez, quotes force exact phrase matching and turn off automatic term mapping, the feature that quietly translates loose queries into indexed ones. A quoted phrase can return less than the same words unquoted. Try both forms. A worked example pulls this together. The query string E. coli (Migula 1895) K-12 contains an abbreviation, an authority, and a strain suffix. Entrez sees several stray terms and returns nothing. The query Escherichia coli returns the species, and from there the K-12 lineage can be reached through the record's subgroups. ## Cause 2: Synonyms, Renamed Taxa, and Merged Taxids Organism names are governed by nomenclature codes that rename taxa constantly. Committees recombine species into different genera, split families, and sink old names into synonymy. NCBI Taxonomy tracks the current view, keeps known old names as synonyms, and merges taxids when nodes combine. Most synonym searches resolve on their own. The failures come from three corners. Old medical names are the classic case. The name Pneumocystis carinii was applied to the fungus found in human patients for decades. The human organism was then renamed Pneumocystis jirovecii, and P. carinii was restricted to the rat-associated species. A search for P. carinii in a human context now points at the wrong taxon, and an old pipeline carrying the old taxid pulls the wrong node. Higher ranks move too. A mitogenomic study of the snail superfamily Truncatelloidea reconstructed relationships across 20 genera from 11 families, described a new genus, and found that the long-accepted genus Assiminea is not monophyletic [2]. When classifications like that settle into the database, older genus-level combinations stop resolving the way the older literature spells them. Retired numbers are the third corner. A merged taxid redirects politely in the browser, but a script that stored the old number can silently resolve to the wrong node or fail outright. Two fixes cover this cause. Open the record for the closest match and read the Synonyms field, which lists every name the database knows for that node. And when you reuse a taxid from an old paper or an old script, check it against merged.dmp and delnodes.dmp from the taxdump archive before you trust it. ## Cause 3: The Name Is New, Provisional, or Was Never Deposited NCBI adds a taxon when the name attaches to submitted sequence data, to a published record the curation process picks up, or to an import from a partner source. A species described in a paper last week may not appear until its sequences and records have been processed. Timing varies. Names attached to submitted sequences usually appear when the sequences are released. Names that exist only in newly published literature wait for curation. There is no fixed schedule, so plan around the parent taxon. The Truncatelloidea study mentioned above described Aenigmula sinensis as a new species, supported by morphology, three gene fragments, and species delimitation analyses [2]. Before its sequences and name were deposited and processed, no search for that string could return anything, because the node did not exist. No syntax trick fixes that. The gap is wider for organisms known only from sequences. A survey of the fungal genus Myochromella mined internal transcribed spacer (ITS) sequences, the standard identification barcode for fungi, from GenBank along with amplicon data (PCR-amplified marker sequences) from the Sequence Read Archive (SRA), the NCBI repository for raw sequencing reads. At a 98 percent sequence similarity threshold the survey recognized eleven species, eight of them without formal designations [3]. Those eight have no scientific name to search. The search is not broken. The names do not exist yet. Provisional names create a related trap. Candidatus taxa are included in the database, but the literature writes them with quotation marks and the database stores them without, so paste the name plainly. Metagenome-assembled genomes (MAGs), which are draft genomes reconstructed from environmental samples without isolating the organism, carry placeholder names that are hard to guess and easy to misspell. If the parent genus resolves but the species does not, open the parent record, browse its subgroups, and look for alternate spellings. If the name is genuinely absent, BLAST (the Basic Local Alignment Search Tool, NCBI's sequence similarity service) a sequence from your organism as described under Cause 5, anchor to the closest named relative, and use the Contact link on the Taxonomy site to ask the curators to consider an addition. ## Cause 4: Strains, Cultivars, and Isolates Are Not Taxa ![Flowchart from species search in Taxonomy to taxid, then a branch into BioSample, Assembly or SRA for the strain or cultivar string.](/article-images/illustrations/ncbi-taxonomy-search-not-working-two-step-strain-lookup.webp) Taxonomy stores organisms at the species rank and above, with a few exceptions. A handful of laboratory lineages, such as the K-12 lineage of Escherichia coli, do exist as taxa. Almost every other strain, isolate, cultivar, and clinical specimen lives in a different database. Isolate metadata lives in BioSample, the NCBI database that stores descriptions of biological source materials. Genome assemblies live in Assembly. Raw reads live in SRA. A cultivar name is a BioSample and SRA fact, not a taxonomy fact. One sesame genomics study shows the split clearly. The authors combined five Egyptian genotypes, including the cultivars Shandaweel 3 and Toshky1 and three gamma-irradiated mutant lines, with 19 publicly available SRA datasets, and compared all 24 genotypes to call 26,424 filtered SNPs [4]. Every cultivar name in that study resolves in SRA and BioSample. None of them is a taxonomy search, and none needs to be. The fix is a two-step query. First resolve the species in Taxonomy and note its taxid. Then search the sequence databases with the taxid filter, for example txid562[orgn] in Assembly or SRA, and add the strain or cultivar string as a second term. In BioSample, search the strain string directly. The same two-step logic covers applied work. A veterinary diagnostic laboratory identifying an isolate from a [dog ear infection](/knowledge/veterinary-medicine/preventive-and-routine-care/dog-ear-infection-spot-when-to-see-vet) resolves Staphylococcus pseudintermedius in Taxonomy, then finds the specific isolate in BioSample by its laboratory identifier. The species is a taxon. The isolate is not, and searching for the isolate number in Taxonomy will always return nothing. ## Cause 5: Uncultured, Environmental, and Metagenomic Names Environmental studies generate enormous numbers of organisms that have never been cultured or formally named. The database stores them under labels like uncultured bacterium and uncultured fungus, plus study-specific clone names, grouped under environmental samples nodes. A name printed in a paper often fails as a search because the paper's label and the database's label differ. The reliable route is sequence based. The 16S rRNA gene, the standard identification marker for bacteria and archaea, and the ITS region for fungi can be amplified and sequenced from almost any sample. Full-length 16S rRNA sequencing on MinION flow cells with taxonomic assignment through NCBI is now a working standard for profiling bacterial communities in human studies [5]. The workflow runs in four steps. 1. Amplify and sequence the marker gene from your organism, 16S for bacteria and archaea, ITS for fungi, and the cytochrome c oxidase I gene (COI) for animals. 2. BLAST the sequence at blast.ncbi.nlm.nih.gov against the dedicated 16S or ITS databases, or against the broad non-redundant databases for a wider net. 3. Take the closest named hit and search that name in Taxonomy. 4. Report the identification with the percent identity, the reference accession, and the similarity threshold you applied. Thresholds are conventions, not laws, so state the one you used and cite the convention you followed. Amplicon studies often report operational taxonomic units (OTUs) or amplicon sequence variants (ASVs) instead of species. Those labels belong to the analysis, not to the taxonomy database, and searching them in Taxonomy fails by design. Map the representative sequence to a named taxon with BLAST first. Safety note: if the sequence comes from a clinical specimen or a culture you isolated yourself, handle the specimen and any cultures under your institution's biosafety procedures, and treat a pathogen identification as preliminary until a qualified microbiologist confirms it. ## Cause 6: Viruses Change Faster Than Names Virus classification follows the International Committee on Taxonomy of Viruses (ICTV), and it moves fast. Species get renamed, genera get reorganized, and newly discovered viruses sit in unclassified nodes, sometimes for years. A search for the exact name of a novel virus usually fails because the virus has no accepted name yet. A virome study of Theobroma cacao shows the pattern. The authors pulled 109 publicly available [RNA sequencing](/blog/guides/rna-sequencing) (RNA-seq) libraries from nine BioProjects, ran a pipeline with viral sequence enrichment, assembly, and similarity searches against the NCBI non-redundant databases, and reported ten putative novel viruses plus a novel Badnavirus species [6]. At discovery time, none of the ten had a searchable taxon. The novel Badnavirus could only be placed relative to the existing Badnavirus node, not found by name. The fixes follow from the mechanism. - Search the highest taxon you trust, the family or the genus, and browse its subgroups for the unclassified containers. - BLAST your sequence and read the taxonomy of the top hits rather than trusting any single label. - Check the current ICTV species list for renames, then search the new name. - Remember that the species node can exist while individual isolates do not. The species Severe acute respiratory syndrome coronavirus 2 sits at taxid 2697049, while isolate names live in the sequence databases. ## Cause 7: You Are Searching the Wrong NCBI Database NCBI is a family of linked databases, and the most common how-to-use-NCBI mistake is asking an organism question in the wrong one. PubMed searches literature. Taxonomy searches names and hierarchy. Nucleotide searches sequences. Assembly searches genome assemblies. SRA searches raw reads. BioSample searches isolate metadata. Gene searches genes. Map the question to the database before you type. | Question | Database to search | |--|--| | What is this organism called and where does it sit in the tree? | Taxonomy | | Which genomes exist for this species? | Assembly | | Which raw reads can I download? | SRA | | Where did this sample come from? | BioSample | | Which genes does this species carry? | Gene | | What has been published about it? | PubMed | You can push a taxonomy filter into most sequence databases with the orgn field tag. The query txid562[orgn] in Nucleotide or Assembly returns records for Escherichia coli and everything below it. The query txid9612[orgn] does the same for the dog, Canis lupus familiaris. Real projects lean on this constantly, and they enter through different doors. A study of avian innate immunity mined genome assemblies across 72 species from 26 orders to map cathelicidin gene clusters, and identified 190 putative cathelicidin genes, 103 of them previously undescribed [7]. That work started from Assembly, filtered by bird taxa, not from Taxonomy alone. A taxonomy-guided natural products review used the opposite route, defining the genus list in the Taxonomy Browser first and then running keyword searches in CAS SciFinder-n and PubMed [1]. Same database family, different entry points, both correct for their goals. The design lesson generalizes to any search. A systematic map of pharmaceutical effects on aquatic animal behavior built its search string around a Population-Exposure-Comparison-Outcome framework, ran it across two literature databases, and screened in two stages [8]. Structured queries beat free-text guesses in every NCBI database, including Taxonomy. When a search in Taxonomy fails but the same string hits Nucleotide or SRA, read the organism line on those records. It names the taxon the sequences were filed under, which is often the answer you were looking for. One diagnostic feature deserves more use than it gets. On any Entrez results page, open the Search details box. It shows exactly how Entrez interpreted your query, including automatic term mapping and the field tags it applied. When a search fails, Search details usually shows why. ## Cause 8: Query Syntax and E-utilities Failures Everything above assumes the web search box. Scripts fail for extra reasons. The Entrez syntax rules that matter in Taxonomy are few and strict. - Boolean operators must be uppercase. Escherichia AND coli works. Escherichia and coli treats and as a stopword and quietly changes the query. - Truncation ends a stem with an asterisk. Entrez requires at least four characters before the asterisk and caps wildcard matches at 600, so a stem like ama* fails on length while bact* hits the cap. - Quotation marks force exact phrase matching and disable automatic term mapping. - Field tags select the search field. In sequence databases, [orgn] filters by organism. The E-utilities, the Entrez Programming Utilities, are the scriptable interface to every NCBI database. A minimal name resolution looks like this. https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=taxonomy&term=Panthera%20leo Spaces must be URL encoded as %20 or plus signs. A call with raw spaces fails. The db parameter must say taxonomy. Pointing esearch at db=pubmed with an organism name is a classic copy-paste error that returns literature IDs instead of taxids. Rate limits are real. NCBI allows three requests per second without an API key and ten per second with one, and it returns error responses when scripts exceed the limit. Get a free API key from your NCBI account settings, append it to each call, and add a delay between requests. To fetch the full record with lineage and synonyms, call efetch on the returned ID. https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=taxonomy&id=9606&retmode=xml In a terminal with the EDirect tools installed, the same two calls pipe together. esearch -db taxonomy -query "Panthera leo" | efetch -db taxonomy -format xml Debug syntax in the browser before you script it. Build the query in the Advanced search builder, confirm it returns the right node, then copy the query string into your code. If esearch in the terminal returns what the browser does not, the problem is the browser layer, not the data. If both fail, the name is genuinely absent or misspelled, and the earlier causes apply. ## A Ten-Step Diagnostic Sequence Run these steps in order and stop at the first one that resolves the name. 1. Paste the plain scientific binomial, with no abbreviations, no authority string, and no strain suffix. 2. Fix spelling and formatting with the sixty-second checklist. 3. Search the genus name alone and scan the species list for near matches and alternate spellings. 4. Try the common name and any known synonyms. 5. Open the Search details box on the results page and read how Entrez interpreted the query. 6. Search the same string in BioSample, Assembly, and SRA. A hit there means the organism exists as an isolate, not as a taxon. 7. Search the parent taxon and browse its subgroups, including the unclassified and environmental samples nodes. 8. BLAST a marker sequence, 16S, ITS, or COI, and search the closest named hit in Taxonomy. 9. Repeat the search through E-utilities to rule out browser problems, and check merged.dmp if you are reusing an old taxid. 10. If every step fails, the name is not in the database. Work from the closest named relative, document the gap, and submit an addition request through the Contact link on the Taxonomy site. Steps 1 through 5 clear the majority of failures. Steps 6 through 9 catch the structural ones. ## Common Mistakes and Limitations These are the errors that cost the most time. - Treating Taxonomy as a registry of all described life. It is a curated database built around sequence data and curated imports, and validly published names can be absent. - Reading a BLAST percent identity as an identification. A high identity score does not by itself make your organism that species. Report the reference accession, the percent identity, and the threshold convention you applied. - Reusing taxids from old papers or old scripts without checking merged.dmp and delnodes.dmp. Merged taxids redirect in the browser and fail silently in scripts. - Putting strain names where taxids belong in a pipeline. Scripts that treat strain strings as taxonomy terms break on the first uncultured or provisional name. - Assuming punctuation is safe. Parentheses, apostrophes, multiplication signs, and accented characters all change what Entrez searches. - Ignoring homonyms (identical names that belong to different organisms). Pieris is both a butterfly genus and a plant genus, and Aotus is both a monkey genus and a legume genus. They carry different taxids, and a name-only search can hand you the wrong one. - Trusting a single verification. Taxonomy changes continuously, so a taxid you confirmed last year can be merged or deleted today. One boundary deserves a plain statement. If a search supports a clinical decision, such as identifying an isolate from a sick animal or a human patient, a veterinarian or clinical microbiologist must confirm the identification before treatment follows from it. ## Prevention Practices That Save Hours Later A few habits prevent almost every failure in this article from recurring. - Record the taxid next to every organism name in your notebook, spreadsheet, or pipeline configuration, along with the date you verified it. - Resolve names programmatically at the start of a pipeline. One esearch call per organism, fail fast on zero hits, and log the taxid. - Keep a copy of the taxdump archive (https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/taxdump.tar.gz) in your project and check merged.dmp and delnodes.dmp whenever you reuse an old taxid. - Pin accession numbers for reference sequences. Accessions are stable in a way that names are not. - Store strain and isolate identifiers in BioSample terms and species identity in taxonomy terms, and never mix the two. - When a name is provisional, record the closest named parent taxid as well, so your pipeline has an anchor while the name catches up. - Re-verify taxids at the start of each analysis cycle rather than once a year. - For large studies, resolve names locally from the taxdump files instead of hammering E-utilities with thousands of requests. The theme is simple. Names are labels that move. Taxids and accession numbers are the stable handles, and the taxdump files are the change log. ## Frequently Asked Questions ### Why is my species in PubMed but not in NCBI Taxonomy? Because Taxonomy is built around sequence data and curated records, while PubMed indexes literature. A name can be published long before any sequence or record carries it into Taxonomy. Search the parent genus in the meantime and BLAST a sequence if you have one. ### How do I find a strain or cultivar that Taxonomy search does not show? Search the species in Taxonomy, note its taxid, then search the strain or cultivar string in BioSample, Assembly, or SRA. Strain-level names live in those databases, not in Taxonomy. ### What is a taxid and why do taxids disappear? A taxid is the unique number NCBI assigns to each node in the taxonomy tree. Taxids are retired when nodes are merged or deleted, and the retired numbers are logged in the merged.dmp and delnodes.dmp files of the taxonomy archive. ### Can I use wildcards in the NCBI Taxonomy search box? Yes. End a stem with an asterisk, use at least four characters before the asterisk, and expect a cap of 600 matches. Lengthen the stem or narrow with AND if the search fails or floods. ### Why does BLAST return a species name that Taxonomy search cannot find? Because BLAST matches sequences, and a sequence may be labeled with a name that is not a taxonomy node, such as an uncultured clone or a provisional isolate. Search the closest named relative instead, and report the percent identity with the reference accession. ### How do I search NCBI Taxonomy from a script? Use the E-utilities. Call esearch with db=taxonomy and a URL-encoded term, then call efetch with the returned ID to get the full record. Add an API key and stay within the rate limits of three requests per second without a key and ten with one. ### Why do I get several different organisms when I search one name? Because the same name can be a homonym across kingdoms or a synonym attached to several nodes. Pieris is both a butterfly and a plant genus. Read the lineage on each hit and disambiguate with the parent name or the taxid. ### How current is NCBI Taxonomy, and how fast do new species appear? The database is updated continuously, but a new species appears only after its sequences and records are deposited and processed. Recently described names can lag by weeks or longer, so anchor to the parent taxon in the interim. ## Sources 1. [The Occurrence and Bioactivities of Amaryllidaceae Alkaloids from Plants: A Taxonomy-Guided Genera-Wide Review.](https://pubmed.ncbi.nlm.nih.gov/40647943/) 2. [Mitogenomic phylogeny of Truncatelloidea with description of Aenigmula sinensis Tang, Han & Kong, sp. nov. (Mollusca, Gastropoda, Littorinimorpha, Truncatelloidea).](https://pubmed.ncbi.nlm.nih.gov/42211056/) 3. [Myochromella unveiled: exploring its global distribution through a public database of amplicons.](https://pubmed.ncbi.nlm.nih.gov/40413396/) 4. [Exploring the genetic landscape of sesame: whole genome sequencing reveals distinct Egyptian lineages and SNP variability.](https://pubmed.ncbi.nlm.nih.gov/41619030/) 5. [In Search of Healthy Ageing: A Microbiome-Based Precision Nutrition Approach for Type 2 Diabetes Prevention.](https://pubmed.ncbi.nlm.nih.gov/40507144/) 6. [Theobroma cacao Virome: Exploring Public RNA-Seq Data for Viral Discovery and Surveillance.](https://pubmed.ncbi.nlm.nih.gov/40431635/) 7. [Exploring diversity in avian immune defence: Insights from cathelicidin clusters.](https://pubmed.ncbi.nlm.nih.gov/40127729/) 8. [Evidence of the impacts of pharmaceuticals on aquatic animal behaviour (EIPAAB): a systematic map and open access database.](https://pubmed.ncbi.nlm.nih.gov/40108717/)