Key | Value |
---|---|
FileSize | 2871720 |
MD5 | ABD154132CFD62B9CD00A13BE04241E0 |
PackageDescription | docs for python-cogent PyCogent is a software library for genomic biology. . It is distinguished by many unique built-in capabilities (such as true codon alignment) and the frequent addition of entirely new methods for the analysis of genomic data. . This package contains documentation and examples. |
PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
PackageName | python-cogent-doc |
PackageSection | doc |
PackageVersion | 1.9-11build1 |
SHA-1 | E1BBB0E4F2CECDD4A8891FD5D46772E61FF9AFAA |
SHA-256 | EB1CB324C51089092365E9EFA9197011FF035754A7D51FD754CE85FB4969D82D |
hashlookup:children-total | 628 |
hashlookup:trust | 50 |
The searched file hash includes 628 children files known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent/tests/test_db/test_ensembl/test_compara.py.gz |
FileSize | 3305 |
MD5 | CBF1AB0A0E4D0E1A70FE830B7B1F11AF |
SHA-1 | 00FBC4BBB4093E90862A03CADEC52C1A5CC71E7E |
SHA-256 | 1F2EB8D5D1983616A84EC1B7CB15F9D4613BC795FDA85C0A05601A09FEF2766F |
SSDEEP | 96:pD7iFvIpmPSNov5pphDJfVJTSmc1fHVLMwDr:p/2vhDW1awDr |
TLSH | T1CA614B5AC2AD77529E40530687E7218A016FC635F584AF01086361CC11B652A24DEDF6 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent-doc/doctrees/cookbook/annotations.doctree.gz |
FileSize | 16209 |
MD5 | 435492A5AA13E9CC5A31D74E64F3F6D1 |
SHA-1 | 00FC3A401A49A79B34C33B60BCFA91AFB847B32D |
SHA-256 | B773D955946F6A4C61DEAA2CD32D84554A06B0081924A8AE02B27B435CA47E61 |
SSDEEP | 384:MUwZ9c4YAVpiceaM/ttkrIcJhsd8YboVXPzsM:5lkqtasJd8YboVoM |
TLSH | T1DA72D0E8D4CAE7A0850B36F12CF0DCF1084A964B5CE1E751DF14028A97C7B9EC55B99A |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent-doc/doctrees/examples/translate_dna.doctree.gz |
FileSize | 2461 |
MD5 | 4903CFC6D6FECFDA572965CE12DB667B |
SHA-1 | 014C5A88E56F616E7C8CBE6C08C60404728F7BE8 |
SHA-256 | B255BCD6DE7963A88014D9505069559BC6B84A4676926ADDF26685E0FDD14E14 |
SSDEEP | 48:Xbpa8qbo0yZsRWX08IcAFY/ou1t99lHVMuJzvGs3mhx+WA7Jpbo9w0b+lE:9a8d0AN76Y/31tnlHVM8zvzJpboYlE |
TLSH | T17C5128795E08007DA654F92EAA8FE1DE0F58D0EE029BE715DD89A41081CDAA6258B938 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent/tests/test_app/test_guppy.py.gz |
FileSize | 1586 |
MD5 | 6C3EE29FCDF6748BA180D27A88B60648 |
SHA-1 | 014EEDED2D64D4316D7A46E80117AD34BD22DCA2 |
SHA-256 | D1DB700F2E6BD77873FF286DD56AAEEA181C65939FFA7186F7D195EE4C5F5184 |
SSDEEP | 48:XDgGsbzp7ctcEmZ5lmtCDzxi9A686ogv9f:TkHZctcFdDzwc6og1f |
TLSH | T1CF31CA8667D2911501C640A257E51D1E9ED33EE94AB654A1ED02D1B87106B3004AF3F9 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent-doc/doctrees/examples/calculate_pairwise_distances.doctree.gz |
FileSize | 3843 |
MD5 | D3CDDBE270382A5B4AAEF2F7EB153147 |
SHA-1 | 01ABA023755C23D411E37F410E4F17A9CBBA2EA7 |
SHA-256 | 00D9318C778623A33AE8E21BB9CDC273D0232C479656F61E371E85F1D87BC5C3 |
SSDEEP | 96:GRolo+1jhu9xHxkQ2cKkI92fFV0oiauurJS1q3buQ:lmekLHxx27PoiauuWKR |
TLSH | T119817E9A557243DCC391CAE64F9DF3BF225748813D958FC4D6158E1111C8CE85D94C8B |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent-doc/html/examples/hmm_par_heterogeneity.html |
FileSize | 34606 |
MD5 | 732A991A283D4DFA1F31738369BC4E4E |
SHA-1 | 025D95DB7A9A0D392D9EFAF1B973137780A1C606 |
SHA-256 | 1396F7D74DDDFB7B6CE115427A406D925FA788F6E7BDE7802A9777BA01A22ADE |
SSDEEP | 768:x9a/S4a2JCIAfVtv0BpvgG+lOsnARTOGYI2NpQ:x9aaYJCIAfrvepvgG+lOsnAYGyO |
TLSH | T1F2F2A0E5EAF79133007BC4C362AE1B75F1E2946AE4960041B2FD97B843DDE41780B96E |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent/tests/benchmark.py.gz |
FileSize | 1888 |
MD5 | BB86EFDA4DC07609E15D696A29FA9839 |
SHA-1 | 0325FC1615E70A37CA9202EA849CCEDFB345E1ED |
SHA-256 | C8FB2365F1AD2270237AE2E7C57767A2716604EA4C6D989B0B3E686C393F36E5 |
SSDEEP | 48:XtMI1BVowx1aY6L03mE1ya7y1dYbO1ACAXUNresIX4:uI1BVviYo1nYSiCAkNCsK4 |
TLSH | T18F41F91A28FD9ABD92D09A70ABEC94D31657D90F84E3805776A63C911EC2C531B8051A |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent-doc/html/cookbook/hpc_environments.html |
FileSize | 6461 |
MD5 | 00907AB388ACF2BF6293E9E75576061B |
SHA-1 | 032DE0A8B9917A0D7BC914095A0BAD6FAA14DCEF |
SHA-256 | D8F04757403AB9CF894E52149EA89596FE82520355B9EE9C8B67FF16D1BE44F4 |
SSDEEP | 96:OXfFFDmbGVXsBPR9D9aKwPC5rK+xFPM/zN2Ti07lDZvD:qFSGEPRDJqsKuB5W07v7 |
TLSH | T16AD184220CE4AC23418346C4AAA5372E7D93E61BC7465D54B0FC52AA5FC3FA1DE1721E |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent-doc/html/cookbook/structural_data.html |
FileSize | 43435 |
MD5 | 0E2A63A0860EDFA1567E491DB9A9D8A8 |
SHA-1 | 04120D6CE7E35DE35D89E2E76F485BC70073458A |
SHA-256 | A0C17445DA25FAEA06B56E25BAB403E609116F7DB8A344FE8F21A3C8B16D4FF1 |
SSDEEP | 768:icoj7EL+V8MgiEII4Nq645ZlZ+qOHNQQjWZiNyMknj:inj7EL+V8MgiEII4Nq645ZlZ+qOHNQQI |
TLSH | T19613DFD1E6F794734077D9D3A2BE2B75B0E2546AE4820441A3FD87B843ECD84B813D6A |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-cogent/tests/test_core/__init__.py |
FileSize | 884 |
MD5 | E0971F013CC8C53EF33A47A853A4DE3C |
SHA-1 | 0424518CCC8F28B3CD3CAAFB93630A9F8F482AE3 |
SHA-256 | AF3532DF903E8901D0AFF33D035D4E6E012C206DC5E5F09AC5BD8C02C2612186 |
SSDEEP | 12:HvRJE8JHoTL/pHH57+7XbSo87hEUtIgMAs831oeJFZGUSHIkbyWXEFotJI6EHHn:PgX5EgnMALHJTcIIyW8KCvHn |
TLSH | T1101147BA541B8E2284C2041BE85D71139AD0C8534CC57113394E1D3E6F9F96FC2F0177 |