Result for 0170D6F3F07FA555B281FC7D1E83EAA4B60046D4

Query result

Key Value
FileName./usr/share/doc/rdkit/html/api/rdkit.VLib.NodeLib.DbMolSupply.DbMolSupplyNode-class.html
FileSize14085
MD5865D49BA7DDAA7675A53EFC5640BCA83
SHA-10170D6F3F07FA555B281FC7D1E83EAA4B60046D4
SHA-256AD40523B413D8410408CECD3D1D155D18D736C88474E00413F06566F2C38E76D
SSDEEP192:t9xDHDX/3NEN1aa6maVRazIokr/xtYDZFndhHDX/3x8rwM9:t9xUngrSB8L9
TLSHT1E9527340D6E1377B662790EAD2E02F9B6ED680ABCB010454B9FD53724F89F84591B43E
hashlookup:parent-total3
hashlookup:trust65

Network graph view

Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize3209362
MD5597A2976EF23A0322B6A01C6E0A12C1F
PackageDescriptionCollection of cheminformatics and machine-learning software RDKit is a Python/C++ based cheminformatics and machine-learning software environment. Features Include: . * Chemical reaction handling and transforms * Substructure searching with SMARTS * Canonical SMILES * Molecule-molecule alignment * Large number of molecular descriptors, including topological, compositional, EState, SlogP/SMR, VSA and Feature-map vectors * Fragmentation using RECAP rules * 2D coordinate generation and depiction, including constrained depiction * 3D coordinate generation using geometry embedding * UFF and MMFF94 forcefields * Chirality support, including calculation of (R/S) stereochemistry codes * 2D pharmacophore searching * Fingerprinting, including Daylight-like, atom pairs, topological torsions, Morgan alogrithm and MACCS keys * Calculation of shape similarity * Multi-molecule maximum common substructure * Machine-learning via clustering and information theory algorithms * Gasteiger-Marsili partial charge calculation . File formats RDKit supports include MDL Mol, PDB, SDF, TDT, SMILES and RDKit binary format.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-rdkit
PackageSectionpython
PackageVersion201503-3
SHA-199F06B377F9CD7EBB67CB8BA5B798A6C1FC8C6FE
SHA-2566D5508F3429AB83273078049B70959A15A0B5EAF61D0A40D0663F26B7ED82000
Key Value
FileSize5455482
MD511312B15A61C6192767D5FDC6DFF1F90
PackageDescriptionCollection of cheminformatics and machine-learning software (documentation) RDKit is a Python/C++ based cheminformatics and machine-learning software environment. . This package contains the documentation.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamerdkit-doc
PackageSectiondoc
PackageVersion201503-3
SHA-130E98E44B610414CF65EE611E79B0C5977E335A5
SHA-2560DE44C8AE3A087A4A0070AE75A227F7345B8C5834C91E3C5B4EB50D5BF898152
Key Value
FileSize3196258
MD563B69830E2562372DC14721D182A96B4
PackageDescriptionCollection of cheminformatics and machine-learning software RDKit is a Python/C++ based cheminformatics and machine-learning software environment. Features Include: . * Chemical reaction handling and transforms * Substructure searching with SMARTS * Canonical SMILES * Molecule-molecule alignment * Large number of molecular descriptors, including topological, compositional, EState, SlogP/SMR, VSA and Feature-map vectors * Fragmentation using RECAP rules * 2D coordinate generation and depiction, including constrained depiction * 3D coordinate generation using geometry embedding * UFF and MMFF94 forcefields * Chirality support, including calculation of (R/S) stereochemistry codes * 2D pharmacophore searching * Fingerprinting, including Daylight-like, atom pairs, topological torsions, Morgan alogrithm and MACCS keys * Calculation of shape similarity * Multi-molecule maximum common substructure * Machine-learning via clustering and information theory algorithms * Gasteiger-Marsili partial charge calculation . File formats RDKit supports include MDL Mol, PDB, SDF, TDT, SMILES and RDKit binary format.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-rdkit
PackageSectionpython
PackageVersion201503-3
SHA-199CE791C1BCEB3EADCAC6338C817FE7F1882DD4F
SHA-25651E5DF9B4AD9A8F2E47FB20EEBF8E8F308B8688B23A1C9054FBE40954806B4AB