Search Results for "genes"
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Showing 258 open source projects for "genes"
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Evolver
The GEP-Powered Self-Evolution Engine for AI Agents
...Its purpose is to turn isolated prompt adjustments into reusable, auditable evolution assets, giving agent teams a more structured way to improve behavior over time. The project uses a protocol-constrained approach centered on concepts such as genes, capsules, and events, which are stored as structured assets and selected through signal matching logic. It also depends on Git as part of its operating model, using repository state for rollback, blast-radius calculation, and solidification workflows, which makes it especially relevant for code-centric agent environments. The CLI integrates with external agent runtimes through setup hooks, including support for platforms such as Cursor, where hooks can fire at specific lifecycle moments like session start or after file edits. -
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OpenMed
Open source healthcare AI
...Its core purpose is to provide specialized medical entity extraction, PII detection and de-identification, assertion-aware analysis, and related healthcare text processing capabilities without locking users into a proprietary platform. The project includes a curated registry of more than a dozen medical NER models focused on areas such as diseases, drugs, anatomy, genes, and protected health information, and it is built to support both research and deployment scenarios. OpenMed can be used in three main ways: as a simple Python API for scripts and notebooks, as a Docker-friendly FastAPI service for backend integration, and as a batch-processing system for multi-document workflows. -
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Prokka
Rapid prokaryotic genome annotation
Prokka is a command-line software tool for rapid annotation of prokaryotic genomes (bacteria and archaea). Given a FASTA file of contigs, it predicts genes, rRNAs, tRNAs, and other functional elements, then assigns functions by comparing to reference protein databases and HMM profiles. It outputs GenBank, GFF, and other formats compatible with downstream tools and genome browsers. Prokka handles common complications—overlapping ORFs, frameshifts, alternate start codons—while providing customizable databases so researchers can bias domain or strain-specific annotations. ... -
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...GeneMiner2: Accurate and automated recovery of genes from genome-skimming data. Molecular Ecology Resources 26: e70111.https://doi.org/10.1111/1755-0998.70111
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FragGeneScan is an application for finding (fragmented) genes in short reads. It can also be applied to predict prokaryotic genes in incomplete assemblies or complete genomes. FragGeneScan was first released through omics website (http://omics.informatics.indiana.edu/FragGeneScan/) in March 2010, where you can find its old releases. FragGeneScan migrated to SourceForge in October, 2013.
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NifFINDER
A preditor of Nif proteins
Tool developed in MATLAB to identify the set of proteins encoded by the nifs genes (which are called Nifs). Niffinder identifies up to 24 Nifs - For each Nif protein an Artificial Neural Network (ANN) was built. -
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popoolation
estimate natural variation and positive selection
PoPoolation is a pipeline for analysing pooled next generation sequencing data. Currently PoPoolation allows to calculate Tajima’s Pi, Watterson’s Theta and Tajima’s D with a sliding window approach for chromosomes or for set of genes. One of the main challenges in population genomics is to identify regions of intererest on a genome wide scale. We believe that PoPoolation will greatly aid this task by allowing a fast and user friendly analysis of NGS data from DNA pools. Documentation: https://sourceforge.net/p/popoolation/wiki/Main/ -
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BRIG is a cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. Please cite the BRIG paper if BRIG is used to generate figures for publications: NF Alikhan, NK Petty, NL Ben Zakour, SA Beatson (2011) BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons, BMC Genomics, 12:402. PMID: 21824423
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MEDe-KIT
Micro Educational and Development Kit (MEDe-KIT)
Micro Educational and Development Kit (MEDe-KIT) is an educational software for storing and viewing information about study material information uploaded to it like images and text descriptions. It uses ODBC for storing uploaded data into local database. Its features also include a genes sequencer for generating combination of DNA and RNA sequence entered. Thanks and hope this is useful for everyone who are interested in science and learning. The project was developed using NetBeans IDE and Java. Default login user name : user Default login password : user -
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In addition to computing co-expression clusters, Maccu fishes potential co-expressed genes for a given bait set. All results can be further processed via graph-level operations so that we can compare graphs based on different reference data.
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In addition to RPKM (Reads Per Kbp per Million reads) values, RACKJ computes read counts for exons and splicing events. In so doing, it is feasible to compare two samples and identify genes with most significant difference in exon(splicing)-level.
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QUAST
Quality Assessment Tool for Genome Assemblies
...For the most up-to-date description, please visit http://quast.sf.net. Below are just some highlights. QUAST computes several well-known metrics, including contig accuracy, the number of genes discovered, N50, and others, as well as introducing new ones, like NA50 (see details in the paper and manual). A comprehensive analysis results in summary tables (in plain text, tab-separated, and LaTeX formats) and colorful plots. The tool also produces web-based reports condensing all information in one easy-to-navigate file. ... -
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MPIGeneNet
Parallel tool to construct gene co-expression networks
MPIGeneNet is a parallel tool to construct gene co-expression networks using Pearson’s correlation and Random Matrix Theory (RMT). This tool takes as input a matrix with the expression values (a float value) for different genes observed from several samples. It is a parallelization of RMTGenNet tool (https://github.com/spficklin/RMTGeneNet). MPIGeneNet integrates the whole procedure of creating the in one program, which makes the tool easier to work with (the users only have to launch the application once) and avoids writing/reading from intermediate files among the modules. -
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miRDeep*
MiRDeep*
Please cite: An, J., Lai, J., Lehman, M.L. and Nelson, C.C. (2013) miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data. Nucleic Acids Res, 41, 727-737. We will create index for you if you tell us your interested species (j.an@qut.edu.au). download command line version "MDS_command_line_Vxx.zip" clicking "Browse All Files" please find miRPlant in sourceforge for plant miRNA prediction. -
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...ShettiMotif can parse large dataset of sequences efficiently. Article: Haitham Sobhy; A bioinformatics pipeline to search functional motifs within whole proteome data; poxviruses a case study; Virus Genes, 2017; doi: 10.1007/s11262-016-1416-9; PMID:
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ARES
Antibiotic Resistance Evolution Simulator
ARES (Antibiotic Resistance Evolution Simulator) is a membrane computing-based model, able to simulate complex biological landscapes. It uses a nested membrane-surroundings entitites scheme formatted in a XML file. The created scenarios emulate entities as: i) Resistance genes, able to detoxify antibiotics. These genes can be located in the plasmid, in conjugative elements or in the chromosome; ii) plasmids and conjugative elements transferring genes between bacterial cells; iii) bacterial cells; iv) individual microbiotas where bacterial species coexist; v) hosts containing the microbiotic ensembles; vi) environment(s) where the hosts are contained. ... -
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Amplicon_Sequencing_Worfklow
Analyzing amplicon data from sequences to stats
This is a collection of scripts and instructions on how to analyzing amplicon sequence data (i.e., 16S, ITS2, & other marker genes). I created this workflow to create a consistent set of methods for analyzing amplicon sequence data, from when you first receive the sequence data to statistical analyses & data visualization. All you need is to have the latest version of R installed, some experience with the command line & shell, and enough memory to run all of the programs. -
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Article has been accepted for publication by the journal, "genes". To view the article, please go to MDPI website; please copy and paste the link "https://www.mdpi.com/2073-4425/14/7/1476/pdf" in web address area. If download is not automatically started, please go to the website by copy and paste the link "https://www.preprints.org/manuscript/202306.0366/v1". And click "peer-reviewed article".
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genppi
GENPPI: standalone software for creating protein interaction networks
Our software GENPPI is efficient because, for example, it creates interaction networks from the central genome of 50 species/lineages of Corynebacterium, with an average size of 2200 genes, in less than 40 minutes, on a conventional computer. Our software is compelling because the interaction networks that it creates reflect evolutionary relationships between species and obtained in Average Nucleotide Identity (ANI) analyzes. Also, It allows the user to define how he intends to explore the PP and CN characteristics through various parameters that let on the creation of customized interaction networks. ... -
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EvidentialGene
Evidence Directed Gene Construction for Eukaryotes
EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see http://arthropods.eugenes.org/EvidentialGene/ Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. ... -
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TransMCL
a noval Transcriptome optimization tool
To improve the quality of transcriptome assembly, we introduce TransMCL, a novel transcriptome optimization tool, to reconstruct full-length coding sequences while eliminating redundancy from assembled transcriptomes. TransMCL employs homologs from closely related species to guide the assembly, clustering raw transcripts from transcriptome data and genes from annotated genomes into hierarchical ortholog groups (HOGs). -
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WES analysis of twenty young women under 35 years old affected by DOR without definite factors damaging ovarian reserve and five women with normal ovarian reserve were performed in this study. As a result, we obtained a set of mutated genes that may be related to DOR, where the missense variant on GPR84 was selected for further study. It is found that GPR84Y370H variant promotes the expression of proinflammatory cytokines (TNF-α, IL-6, IL12B, IL-1β) and chemokines (CCL2, CCL5), as well as the activation of NF-κB signaling pathway. Conclusion: In conclusion, GPR84Y370H variant was identified though analysis for WES results of 20 DOR patients. ...
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rafah
Random Forest Assignment of Hosts
...To tackle this issue we developed a machine-learning approach named Random Forest Assignment of Hosts (RaFAH), which outperformed other methods for virus-host prediction. Our rationale was that the machine could learn the associations between genes and hosts much more efficiently than a human, while also using the information contained in the hypothetical proteins. Random forest models were built using the Ranger package in R. -
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RIFTT
Robust identification of fusion genes in tumor transcriptomes.
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Fusion Detection Pipeline
Fusion gene detection pipeline bundled into a Singularity container.
...Our filtering pipeline uses read counts generated by FeatureCounts and insert size estimation by Picard Tools for calculation of our filtering metrics: Fusion Transcript Score (FTS). Further filtering is realized by a custom blacklist, our Promiscuity Score (PS) and Robustness Score (RS). Identified fusion genes are reported with evidence levels based on our filtering. This pipeline has been developed and optimized in a study of 806 AML patient samples (https://doi.org/10.3324/haematol.2021.278436).
