Search Results for "model-builder"
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Showing 33 open source projects for "model-builder"
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AlphaGenome
Programmatic access to the AlphaGenome model
The model analyzes DNA sequences of up to 1 million base pairs in length and can deliver predictions at single-base-pair resolution for most outputs. AlphaGenome achieves state-of-the-art performance across a range of genomic prediction benchmarks, including numerous diverse variant effect prediction tasks. -
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Evo 2
Genome modeling and design across all domains of life
...The codebase is focused on local inference and generation through the Vortex inference stack rather than serving as a full training framework alone, although it also points users to training and fine-tuning resources. It supports multiple ways of working with the model, including forward passes, embeddings, generation workflows, notebooks, hosted APIs, and self-hosted deployment through NVIDIA NIM. -
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BioNeMo
BioNeMo Framework: For building and adapting AI models
BioNeMo is an AI-powered framework developed by NVIDIA for protein and molecular generation using deep learning models. It provides researchers and developers with tools to design, analyze, and optimize biological molecules, aiding in drug discovery and synthetic biology applications. -
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BioEmu
Inference code for scalable emulation of protein equilibrium ensembles
Biomolecular Emulator (BioEmu for short) is a model that samples from the approximated equilibrium distribution of structures for a protein monomer, given its amino acid sequence. By default, unphysical structures (steric clashes or chain discontinuities) will be filtered out, so you will typically get fewer samples in the output than requested. The difference can be very large if your protein has large disordered regions, which are very likely to produce clashes. -
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Protenix
A trainable PyTorch reproduction of AlphaFold 3
Protenix is an open-source, trainable PyTorch reimplementation of AlphaFold 3, developed by ByteDance with the goal of democratizing high-accuracy protein structure prediction for computational biology and drug-discovery research. Protenix provides a complete pipeline for turning protein sequences (with optional MSA / sequence alignment) or structural inputs (e.g. PDB/CIF) into full 3D atomic-level structure predictions. It supports both “full” models and lightweight variants such as... -
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relax
Molecular dynamics by NMR data analysis
...It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using anisotropic NMR parameters such as RDCs and PCSs, the investigation of stereochemistry in dynamic ensembles, and the analysis of relaxation dispersion data. -
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MiModD
Mutation Identification in Model Organism Genomes using Desktop PCs
MiModD is a software package for genomic variant identification from next-generation sequencing (NGS) data with optimized usage of system resources and a user-friendly interface. For most model organism genomes it lets the user carry out a complete analysis from unaligned genomic NGS read data to an annotated list of variants on a regular Desktop PC within a few hours. Its user-interface is beginner-friendly and designed to encourage geneticists to analyze NGS data themselves without the help of a trained bioinformatician. -
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MAGeCK
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
MAGeCK2 is here: https://github.com/davidliwei/mageck2 Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. ... -
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CBMPy
PySCeS Constraint Based Modelling
...Its architecture is both extensible and flexible using data structures that are intuitive to the biologist while transparently translating these into the underlying mathematical structures. . CBMPy implements popular analyses such as FBA, FVA, element/charge balancing, network analysis and model editing as well as advanced methods developed for the ecosystem modelling. CBMPy supports user interaction via: - interactive console or as a library for advanced use - GUI, visual representation of the model, analysis methods - a SOAP based webAPI exposes high level functionality via web services -
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PBTK Optimizer
Application for optimization of parameters in PBTK models
...This tool was designed to optimize a user-specified list of parameters to a user-specified PBTK model. The user also controls validation data and optimization algorithms. In addition to optimized parameters, the tool outputs statistical information about the fit of the optimized model. -
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RELEASE NOTE: Get raxmlGUI 2.0 at the NEW PROJECT LOCATION: https://antonellilab.github.io/raxmlGUI/ raxmlGUI is a graphical user interface to RAxML, one of the most popular and widely used software for phylogenetic inference using maximum likelihood. A userfriendly graphical front-end for phylogenetic analyses using RAxML (Stamatakis, 2006). Please cite: Silvestro, Michalak (2012) - raxmlGUI: a graphical front-end for RAxML. Organisms Diversity and Evolution 12, 335-337. DOI:...
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DualTranscriptDiscovery
Transcript-discovery approach for gene feature delimitation by RNA-seq
This project contains Python scripts usable for a dual transcript-discovery approach that improves the delimitation of gene features from RNA-seq data in the chicken model. Documentation: http://bio.biologists.org/content/biolopen/suppl/2018/01/17/bio.028498.DC1/BIO028498supp.pdf Citation: Orgeur M., Martens M., Börno S. T., Timmermann B., Duprez D. and Stricker S. (2018). A dual transcript-discovery approach to improve the delimitation of gene features from RNA-seq data in the chicken model. ... -
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ABC-SysBio implements likelihood free parameter inference and model selection in dynamical systems. It is designed to work with both stochastic and deterministic models written in Systems Biology Markup Language (SBML).
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nmr-nessy
NMR relaxation dispersion spectroscopy analysis software
...The graphical interface enables simple management of large experimental data sets and simple and automated analysis. NESSY automatically calculates effective transverse relaxation rate (R2eff) and performs model selection between different relaxation dispersion models. -
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SnowyOwl
RNA-Seq based gene prediction pipeline for fungal genomes
SnowyOwl is a gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions, and to evaluate the resulting models. The pipeline has been validated and streamlined by comparing its predictions to manually curated gene models in three fungal genomes, and its results show substantial increases in sensitivity and selectivity over previous gene predictions. Sensitivity is gained by repeatedly running the HMM gene predictor Augustus with varied input parameters, and selectivity by choosing the models with best homology to known proteins and best agreement to the RNA-Seq data. ... -
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pybrn is a Python package for the analysis of biochemical reaction networks. It provides basic model handling capabilities, import from SBML, analysis of conservation relations, steady state computation and model simulation.
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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pyQPCR is a GUI application written in python that deals with quantitative PCR (QPCR) raw data. Using quantification cycle values extracted from QPCR instruments, it uses a proven and universally applicable model to give finalized quantification resu
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Stochastic Rule Builder (SRB)
Modeling framework for capturing positional and temporal dynamics
...Our framework describes individual regulatory components using generic action oriented descriptions of their biochemical interactions with a DNA sequence. All the possible actions are based on the current state of factors bound to the DNA. We developed a rule builder to automatically generate the complete set of biochemical interaction rules for any given DNA sequence. Off-the-shelf stochastic simulation engines can model the behavior of a system of rules and the resulting changes in the configuration of bound factors can be visualized. -
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memesa-tools
A collection of tools used in the enumeration of solution spaces
This collection of tools forms the basis of a pipeline for the complete enumeration of the number of solutions present in a model that maximizes a single objective function. -
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Virus QSP Modeling
C++ and Python code for simulating RNA virus replication
Stochastic simulation model of poliovirus Sabin-to-Mahoney genetic state transition (C++ code). Models genotypes, virus populations, and quasispecies cloud. Simulates replication error and copy-choice recombination. Various parameters guiding the model are user-specified. Python code post-processes simulation output to produce report files. -
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SeqSelector
Tools to select sequences for capture enrichment of next-gen libraries
The SeqSelector toolset is a suite of user-friendly, platform independent python scripts to facilitate selection of sequences for targeted enrichment of next-generation libraries through hybridization-based sequence capture. The scripts require no knowledge of programming, and can be applied to genome sequences of model or non-model species. We suggest a workflow in which genes of interest are first identified from previous studies and publicly available datasets of functional gene annotation. Once a list of candidate genes has been identified, their sequences are selected from the reference genome. These sequences are used as a query during a BLAST search of the unannotated genome of a non-model species, and then the corresponding sequences are returned, which can be used to design baits for hybridization-based sequence capture. -
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WISP
Weighted Implementation of Suboptimal Paths (WISP)
UPDATE: LATEST VERSION AT http://git.durrantlab.com//jdurrant/wisp Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site often many angstroms away. Traditionally, computational efforts have focused on the most optimal path of correlated motions leading from the allosteric to the primary active site. We present a program called Weighted Implementation of Suboptimal Paths (WISP) capable of rapidly identifying additional suboptimal pathways that may also play important roles in the transmission of allosteric signals. ... -
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DeDAY
MLE survival analysis: Gompertz, Weibull, Logistic and mixed morality.
...Mixed models partition mortality into exogenous and endogenous components, so that the intrinsic survivorship can be estimated without the interference from extrinsic noise. DeDAY supports both interval-censored data and exact event-time data. Using MLE (Maximum Likelihood Estimate), DeDAY fits statistic model to the data. DeDAY also calculates the variances and the multi-dimensional confidence limits of model parameters. DeDAY is free for academic users. -
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hrefinder
Detection of homologous recombination events from SNP data
...Based on SNP alleles calls and locations, it breaks the genomes into locally colinear blocks, and looks for cases where SNPs do not agree with the vertical pattern of inheritance in a phylogeny. It applies a dynamic programming algorithm to model whether changes within a block are likely a result of mutations, sequencing errors, or HRE. We use information from the nearby SNPs, so that if 1-2 alleles in a series of SNPs differs from the ancestral allele, it may be better explained as a mutation or sequencing error. But if a series of SNP alleles differ from the ancestral pattern, then it may be more likely that an HRE has occurred, particularly if the allele pattern matches that from another part of the tree better than that of the ancestral node.
