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23
24 """Module containing the introductory text container."""
25
26
27 import dep_check
28
29
30 if dep_check.ctypes_module:
31 import ctypes
32 if hasattr(ctypes, 'windll'):
33 import ctypes.wintypes
34 else:
35 ctypes = None
36 if dep_check.ctypes_structure_module:
37 from ctypes import Structure
38 else:
39 Structure = object
40 from os import environ, pathsep, waitpid
41 import platform
42 from re import search, sub
43 PIPE, Popen = None, None
44 if dep_check.subprocess_module:
45 from subprocess import PIPE, Popen
46 import sys
47 from textwrap import wrap
48
49
50 from status import Status; status = Status()
51 from version import repo_head, repo_type, repo_url, version, version_full
52
53
62
63
64
66 """A container storing information about relax."""
67
68
69 instance = None
70
72 """Create the program introduction text stings.
73
74 This class generates a container with the following objects:
75 - title: The program title 'relax'
76 - version: For example 'repository commit' or '1.3.8'.
77 - desc: The short program description.
78 - copyright: A list of copyright statements.
79 - licence: Text pertaining to the licencing.
80 - errors: A list of import errors.
81 """
82
83
84 self.title = "relax"
85 self.version = version
86
87
88 self.website = "http://www.nmr-relax.com"
89
90
91 self.desc = "Molecular dynamics by NMR data analysis"
92
93
94 self.desc_long = "The program relax is designed for the study of the dynamics of proteins or other macromolecules though the analysis of experimental NMR data. It is a community driven project created by NMR spectroscopists for NMR spectroscopists. It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, and the Lipari and Szabo model-free analysis."
95
96
97 self.copyright_final_year = 2019
98 self.copyright = []
99 self.copyright.append("Copyright (C) 2001-2006 Edward d'Auvergne")
100 self.copyright.append("Copyright (C) 2006-%s the relax development team" % self.copyright_final_year)
101 self.copyright_short = "Copyright (C) 2001-%s the relax development team" % self.copyright_final_year
102 self.copyright_latex = "Copyright \copyright\ 2001-%s the relax development team" % self.copyright_final_year
103
104
105 self.licence = "This is free software which you are welcome to modify and redistribute under the conditions of the GNU General Public License (GPL), Version 3 or any later version published by the Free Software Foundation. This program, including all modules, is licensed under the GPL and comes with absolutely no warranty. For details type 'GPL' within the relax prompt."
106
107
108 self.errors = []
109 if not dep_check.C_module_exp_fn:
110 self.errors.append(dep_check.C_module_exp_fn_mesg)
111
112
113 self._setup_references()
114
115
116 - def __new__(self, *args, **kargs):
117 """Replacement function for implementing the singleton design pattern."""
118
119
120 if self.instance is None:
121 self.instance = object.__new__(self, *args, **kargs)
122
123
124 return self.instance
125
126
146
147
148 - def centre(self, string, width=100):
149 """Format the string to be centred to a certain number of spaces.
150
151 @param string: The string to centre.
152 @type string: str
153 @keyword width: The number of characters to centre to.
154 @type width: int
155 @return: The centred string with leading whitespace added.
156 @rtype: str
157 """
158
159
160 spaces = int((width - len(string)) / 2)
161
162
163 string = spaces * ' ' + string
164
165
166 return string
167
168
170 """Return a string representation of the file type.
171
172 @param path: The full path of the file to return information about.
173 @type path: str
174 @return: The single line file type information string.
175 @rtype: str
176 """
177
178
179 if Popen == None:
180 return ''
181
182
183 pipe = Popen('file --help', shell=True, stdout=PIPE, stderr=PIPE, close_fds=False)
184 err = pipe.stderr.readlines()
185 if err:
186 return ''
187
188
189 cmd = "file -b '%s'" % path
190
191
192 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
193 if not hasattr(ctypes, 'windll'):
194 waitpid(pipe.pid, 0)
195
196
197 data = pipe.stdout.readlines()
198
199
200 if data[0][:-1] == 'Mach-O universal binary with 3 architectures':
201
202 arch = [None, None, None]
203 for i in range(3):
204 row = data[i+1].split('\t')
205 arch[i] = row[1][:-1]
206 arch.sort()
207
208
209 if arch == ['Mach-O 64-bit executable x86_64', 'Mach-O executable i386', 'Mach-O executable ppc']:
210 file_type = '3-way exec (i386, ppc, x86_64)'
211 elif arch == ['Mach-O 64-bit bundle x86_64', 'Mach-O bundle i386', 'Mach-O bundle ppc']:
212 file_type = '3-way bundle (i386, ppc, x86_64)'
213 elif arch == ['Mach-O 64-bit dynamically linked shared library x86_64', 'Mach-O dynamically linked shared library i386', 'Mach-O dynamically linked shared library ppc']:
214 file_type = '3-way lib (i386, ppc, x86_64)'
215 elif arch == ['Mach-O 64-bit object x86_64', 'Mach-O object i386', 'Mach-O object ppc']:
216 file_type = '3-way obj (i386, ppc, x86_64)'
217 else:
218 file_type = '3-way %s' % arch
219
220
221 elif data[0][:-1] == 'Mach-O universal binary with 2 architectures':
222
223 arch = [None, None]
224 for i in range(2):
225 row = data[i+1].split('\t')
226 arch[i] = row[1][:-1]
227 arch.sort()
228
229
230 if arch == ['Mach-O executable i386', 'Mach-O executable ppc']:
231 file_type = '2-way exec (i386, ppc)'
232 elif arch == ['Mach-O bundle i386', 'Mach-O bundle ppc']:
233 file_type = '2-way bundle (i386, ppc)'
234 elif arch == ['Mach-O dynamically linked shared library i386', 'Mach-O dynamically linked shared library ppc']:
235 file_type = '2-way lib (i386, ppc)'
236 elif arch == ['Mach-O object i386', 'Mach-O object ppc']:
237 file_type = '2-way obj (i386, ppc)'
238 else:
239 file_type = '2-way %s' % arch
240
241
242 else:
243 file_type = data[0][:-1]
244 for i in range(1, len(data)):
245 row = data[i].split('\t')
246 arch[i] = row[1][:-1]
247 file_type += " %s" % arch
248
249
250 if file_type == None:
251 return ''
252 return file_type
253
254
278
279
280 - def intro_text(self):
281 """Create the introductory string for STDOUT printing.
282
283 This text is word-wrapped to a fixed width of 100 characters (or 80 on MS Windows).
284
285
286 @return: The introductory string.
287 @rtype: str
288 """
289
290
291 intro_string = '\n\n\n'
292
293
294 if version == 'repository commit':
295 if repo_type == 'git':
296 text = "%s %s" % (self.title, self.version)
297 text2 = "%s" % repo_head
298 else:
299 text = "%s %s r%s" % (self.title, self.version, repo_head)
300 text2 = "%s" % repo_url
301 intro_string += self.centre(text, status.text_width) + '\n' + self.centre(text2, status.text_width) + '\n'
302 if repo_type == 'git':
303 for url in repo_url.split('\n'):
304 intro_string += self.centre(url, status.text_width) + '\n'
305 intro_string += '\n'
306
307
308 else:
309 text = "%s %s" % (self.title, self.version)
310 intro_string = intro_string + self.centre(text, status.text_width) + '\n\n'
311
312
313 intro_string = intro_string + self.centre(self.desc, status.text_width) + '\n\n'
314
315
316 for i in range(len(self.copyright)):
317 intro_string = intro_string + self.centre(self.copyright[i], status.text_width) + '\n'
318 intro_string = intro_string + '\n'
319
320
321 for line in wrap(self.licence, status.text_width):
322 intro_string = intro_string + line + '\n'
323 intro_string = intro_string + '\n'
324
325
326 help = "Assistance in using the relax prompt and scripting interface can be accessed by typing 'help' within the prompt."
327 for line in wrap(help, status.text_width):
328 intro_string = intro_string + line + '\n'
329
330
331 for i in range(len(self.errors)):
332 intro_string = intro_string + '\n' + self.errors[i] + '\n'
333 intro_string = intro_string + '\n'
334
335
336 if hasattr(self, 'multi_processor_string'):
337 for line in wrap('Processor fabric: %s\n' % self.multi_processor_string, status.text_width):
338 intro_string = intro_string + line + '\n'
339
340
341 return intro_string
342
343
554
555
557 """Return a string for the processor name.
558
559 @return: The processor name, in much more detail than platform.processor().
560 @rtype: str
561 """
562
563
564 if Popen == None:
565 return ""
566
567
568 if not dep_check.subprocess_module:
569 return ""
570
571
572 system = platform.system()
573
574
575 if system == 'Linux':
576
577 cmd = "cat /proc/cpuinfo"
578
579
580 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
581 waitpid(pipe.pid, 0)
582
583
584 data = pipe.stdout.readlines()
585
586
587 for line in data:
588
589 if hasattr(line, 'decode'):
590 line = line.decode()
591
592
593 if search("model name", line):
594
595 name = sub(".*model name.*:", "", line, 1)
596 name = name.strip()
597
598
599 return name
600
601
602 if system == 'Windows' or system == 'Microsoft':
603 return platform.processor()
604
605
606 if system == 'Darwin':
607
608 environ['PATH'] += pathsep + '/usr/sbin'
609
610
611 cmd = "sysctl -n machdep.cpu.brand_string"
612
613
614 try:
615
616 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
617 waitpid(pipe.pid, 0)
618
619
620 data = pipe.stdout.readlines()
621
622
623 string = data[0]
624 if hasattr(string, 'decode'):
625 string = string.decode()
626
627
628
629 return string.strip()
630
631
632 except:
633 return ""
634
635
636 return ""
637
638
639 - def ram_info(self, format=" %-25s%s\n"):
640 """Return a string for printing to STDOUT with info from the Python packages used by relax.
641
642 @keyword format: The formatting string.
643 @type format: str
644 @return: The info string.
645 @rtype: str
646 """
647
648
649 if Popen == None:
650 return ''
651
652
653 text = ''
654
655
656 system = platform.system()
657
658
659 if system == 'Linux':
660 pipe = Popen('free -m', shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, close_fds=False)
661 free_lines = pipe.stdout.readlines()
662 if free_lines:
663
664 for line in free_lines:
665
666 row = line.split()
667
668
669 if row[0] == 'Mem:':
670 text += format % ("Total RAM size: ", row[1], "Mb")
671
672
673 if row[0] == 'Swap:':
674 text += format % ("Total swap size: ", row[1], "Mb")
675
676
677 if system == 'Windows' or system == 'Microsoft':
678
679 mem = MemoryStatusEx()
680
681
682 text += format % ("Total RAM size: ", mem.ullTotalPhys / 1024.**2, "Mb")
683
684
685 text += format % ("Total swap size: ", mem.ullTotalVirtual / 1024.**2, "Mb")
686
687
688 if system == 'Darwin':
689
690 environ['PATH'] += pathsep + '/usr/sbin'
691
692
693 cmd = "sysctl -n hw.physmem"
694 cmd2 = "sysctl -n hw.memsize"
695
696
697 try:
698
699 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
700 waitpid(pipe.pid, 0)
701
702
703 data = pipe.stdout.readlines()
704
705
706 pipe = Popen(cmd2, shell=True, stdout=PIPE, close_fds=False)
707 waitpid(pipe.pid, 0)
708
709
710 data2 = pipe.stdout.readlines()
711
712
713 ram = int(data[0].strip())
714 total = int(data2[0].strip())
715 swap = total - ram
716
717
718 text += format % ("Total RAM size: ", ram / 1024.**2, "Mb")
719
720
721 text += format % ("Total swap size: ", swap / 1024.**2, "Mb")
722
723
724 except:
725 pass
726
727
728 if not text:
729 text += format % ("Total RAM size: ", "?", "Mb")
730 text += format % ("Total swap size: ", "?", "Mb")
731
732
733 return text
734
735
785
786
788 """Return a string for printing to STDOUT with info about the current relax instance.
789
790 @return: The info string.
791 @rtype: str
792 """
793
794
795 text = ''
796
797
798 format = " %-25s%s\n"
799 format2 = " %-25s%s %s\n"
800
801
802 text = text + ("\nHardware information:\n")
803 if hasattr(platform, 'machine'):
804 text = text + (format % ("Machine: ", platform.machine()))
805 if hasattr(platform, 'processor'):
806 text = text + (format % ("Processor: ", platform.processor()))
807 text = text + (format % ("Processor name: ", self.processor_name()))
808 text = text + (format % ("Endianness: ", sys.byteorder))
809 text = text + self.ram_info(format=format2)
810
811
812 text = text + ("\nOperating system information:\n")
813 if hasattr(platform, 'system'):
814 text = text + (format % ("System: ", platform.system()))
815 if hasattr(platform, 'release'):
816 text = text + (format % ("Release: ", platform.release()))
817 if hasattr(platform, 'version'):
818 text = text + (format % ("Version: ", platform.version()))
819 if hasattr(platform, 'win32_ver') and platform.win32_ver()[0]:
820 text = text + (format % ("Win32 version: ", (platform.win32_ver()[0] + " " + platform.win32_ver()[1] + " " + platform.win32_ver()[2] + " " + platform.win32_ver()[3])))
821 if hasattr(platform, 'linux_distribution') and platform.linux_distribution()[0]:
822 text = text + (format % ("GNU/Linux version: ", (platform.linux_distribution()[0] + " " + platform.linux_distribution()[1] + " " + platform.linux_distribution()[2])))
823 if hasattr(platform, 'mac_ver') and platform.mac_ver()[0]:
824 text = text + (format % ("Mac version: ", (platform.mac_ver()[0] + " (" + platform.mac_ver()[1][0] + ", " + platform.mac_ver()[1][1] + ", " + platform.mac_ver()[1][2] + ") " + platform.mac_ver()[2])))
825 if hasattr(platform, 'dist'):
826 text = text + (format % ("Distribution: ", (platform.dist()[0] + " " + platform.dist()[1] + " " + platform.dist()[2])))
827 if hasattr(platform, 'platform'):
828 text = text + (format % ("Full platform string: ", (platform.platform())))
829 if hasattr(ctypes, 'windll'):
830 text = text + (format % ("Windows architecture: ", (self.win_arch())))
831
832
833 text = text + ("\nPython information:\n")
834 if hasattr(platform, 'architecture'):
835 text = text + (format % ("Architecture: ", (platform.architecture()[0] + " " + platform.architecture()[1])))
836 if hasattr(platform, 'python_version'):
837 text = text + (format % ("Python version: ", platform.python_version()))
838 if hasattr(platform, 'python_branch'):
839 text = text + (format % ("Python branch: ", platform.python_branch()))
840 if hasattr(platform, 'python_build'):
841 text = text + ((format[:-1]+', %s\n') % ("Python build: ", platform.python_build()[0], platform.python_build()[1]))
842 if hasattr(platform, 'python_compiler'):
843 text = text + (format % ("Python compiler: ", platform.python_compiler()))
844 if hasattr(platform, 'libc_ver'):
845 text = text + (format % ("Libc version: ", (platform.libc_ver()[0] + " " + platform.libc_ver()[1])))
846 if hasattr(platform, 'python_implementation'):
847 text = text + (format % ("Python implementation: ", platform.python_implementation()))
848 if hasattr(platform, 'python_revision'):
849 text = text + (format % ("Python revision: ", platform.python_revision()))
850 if sys.executable:
851 text = text + (format % ("Python executable: ", sys.executable))
852 if hasattr(sys, 'flags'):
853 text = text + (format % ("Python flags: ", sys.flags))
854 if hasattr(sys, 'float_info'):
855 text = text + (format % ("Python float info: ", sys.float_info))
856 text = text + (format % ("Python module path: ", sys.path))
857
858
859 text = text + self.package_info()
860
861
862 text = text + "\nrelax information:\n"
863 text = text + (format % ("Version: ", version_full()))
864 if hasattr(self, "multi_processor_string"):
865 text += format % ("Processor fabric: ", self.multi_processor_string)
866
867
868 text = text + self.relax_module_info()
869
870
871 text = text + ("\n")
872
873
874 return text
875
876
878 """Determine the MS Windows architecture.
879
880 @return: The architecture string.
881 @rtype: str
882 """
883
884
885 if 'PROCESSOR_ARCHITEW6432' in environ:
886 arch = environ['PROCESSOR_ARCHITEW6432']
887
888
889 else:
890 arch = environ['PROCESSOR_ARCHITECTURE']
891
892
893 return arch
894
895
896
898 """Special object for obtaining hardware info in MS Windows."""
899
900 if hasattr(ctypes, 'windll'):
901 _fields_ = [
902 ('dwLength', ctypes.wintypes.DWORD),
903 ('dwMemoryLoad', ctypes.wintypes.DWORD),
904 ('ullTotalPhys', ctypes.c_ulonglong),
905 ('ullAvailPhys', ctypes.c_ulonglong),
906 ('ullTotalPageFile', ctypes.c_ulonglong),
907 ('ullAvailPageFile', ctypes.c_ulonglong),
908 ('ullTotalVirtual', ctypes.c_ulonglong),
909 ('ullAvailVirtual', ctypes.c_ulonglong),
910 ('ullExtendedVirtual', ctypes.c_ulonglong),
911 ]
912
914 """Set up the information and handle non MS Windows systems."""
915
916
917 if hasattr(ctypes, 'windll'):
918 self.dwLength = ctypes.sizeof(self)
919 ctypes.windll.kernel32.GlobalMemoryStatusEx(ctypes.byref(self))
920
921
922
924 """Reference base class."""
925
926
927 type = None
928 author = None
929 author2 = None
930 title = None
931 status = None
932 journal = None
933 journal_full = None
934 volume = None
935 number = None
936 doi = None
937 pubmed_id = None
938 url = None
939 pages = None
940 year = None
941
942
944 """Generate some variables on the fly.
945
946 This is only called for objects not found in the class.
947
948 @param name: The name of the object.
949 @type name: str
950 @raises AttributeError: If the object cannot be created.
951 @returns: The generated object.
952 @rtype: anything
953 """
954
955
956 if name in ['page_first', 'page_last']:
957
958 if not self.pages:
959 return None
960
961
962 vals = self.pages.split('-')
963
964
965 if len(vals) == 1:
966 return vals[0]
967
968
969 if name == 'page_first':
970 return vals[0]
971
972
973 if name == 'page_last':
974 return vals[1]
975
976 raise AttributeError(name)
977
978
979 - def cite_short(self, author=True, title=True, journal=True, volume=True, number=True, pages=True, year=True, doi=True, url=True, status=True):
980 """Compile a short citation.
981
982 The returned text will have the form of:
983
984 - d'Auvergne, E.J. and Gooley, P.R. (2008). Optimisation of NMR dynamic models I. Minimisation algorithms and their performance within the model-free and Brownian rotational diffusion spaces. J. Biomol. NMR, 40(2), 107-119.
985
986
987 @keyword author: The author flag.
988 @type author: bool
989 @keyword title: The title flag.
990 @type title: bool
991 @keyword journal: The journal flag.
992 @type journal: bool
993 @keyword volume: The volume flag.
994 @type volume: bool
995 @keyword number: The number flag.
996 @type number: bool
997 @keyword pages: The pages flag.
998 @type pages: bool
999 @keyword year: The year flag.
1000 @type year: bool
1001 @keyword doi: The doi flag.
1002 @type doi: bool
1003 @keyword url: The url flag.
1004 @type url: bool
1005 @keyword status: The status flag. This will only be shown if not 'published'.
1006 @type status: bool
1007 @return: The full citation.
1008 @rtype: str
1009 """
1010
1011
1012 cite = ''
1013 if author and self.author and hasattr(self, 'author'):
1014 cite = cite + self.author
1015 if year and self.year and hasattr(self, 'year'):
1016 cite = cite + ' (' + repr(self.year) + ').'
1017 if title and self.title and hasattr(self, 'title'):
1018 cite = cite + ' ' + self.title
1019 if journal and self.journal and hasattr(self, 'journal'):
1020 cite = cite + ' ' + self.journal + ','
1021 if volume and self.volume and hasattr(self, 'volume'):
1022 cite = cite + ' ' + self.volume
1023 if number and self.number and hasattr(self, 'number'):
1024 cite = cite + '(' + self.number + '),'
1025 if pages and self.pages and hasattr(self, 'pages'):
1026 cite = cite + ' ' + self.pages
1027 if doi and self.doi and hasattr(self, 'doi'):
1028 cite = cite + ' (http://dx.doi.org/'+self.doi + ')'
1029 if url and self.url and hasattr(self, 'url'):
1030 cite = cite + ' (' + self.url + ')'
1031 if status and hasattr(self, 'status') and self.status != 'published':
1032 cite = cite + ' (' + self.status + ')'
1033
1034
1035 if cite[-1] != '.':
1036 cite = cite + '.'
1037
1038
1039 return cite
1040
1041
1042 - def cite_html(self, author=True, title=True, journal=True, volume=True, number=True, pages=True, year=True, doi=True, url=True, status=True):
1043 """Compile a citation for HTML display.
1044
1045 @keyword author: The author flag.
1046 @type author: bool
1047 @keyword title: The title flag.
1048 @type title: bool
1049 @keyword journal: The journal flag.
1050 @type journal: bool
1051 @keyword volume: The volume flag.
1052 @type volume: bool
1053 @keyword number: The number flag.
1054 @type number: bool
1055 @keyword pages: The pages flag.
1056 @type pages: bool
1057 @keyword year: The year flag.
1058 @type year: bool
1059 @keyword doi: The doi flag.
1060 @type doi: bool
1061 @keyword url: The url flag.
1062 @type url: bool
1063 @keyword status: The status flag. This will only be shown if not 'published'.
1064 @type status: bool
1065 @return: The full citation.
1066 @rtype: str
1067 """
1068
1069
1070 cite = ''
1071 if author and hasattr(self, 'author') and self.author:
1072 cite = cite + self.author
1073 if year and hasattr(self, 'year') and self.year:
1074 cite = cite + ' (' + repr(self.year) + ').'
1075 if title and hasattr(self, 'title') and self.title:
1076 cite = cite + ' ' + self.title
1077 if journal and hasattr(self, 'journal') and self.journal:
1078 cite = cite + ' <em>' + self.journal + '</em>,'
1079 if volume and hasattr(self, 'volume') and self.volume:
1080 cite = cite + ' <strong>' + self.volume + '</strong>'
1081 if number and hasattr(self, 'number') and self.number:
1082 cite = cite + '(' + self.number + '),'
1083 if pages and hasattr(self, 'pages') and self.pages:
1084 cite = cite + ' ' + self.pages
1085 if doi and hasattr(self, 'doi') and self.doi:
1086 cite = cite + ' (<a href="http://dx.doi.org/%s">abstract</a>)' % self.doi
1087 if url and hasattr(self, 'url') and self.url:
1088 cite = cite + ' (<a href="%s">url</a>)' % self.url
1089 if status and hasattr(self, 'status') and self.status != 'published':
1090 cite = cite + ' (<i>%s</i>)' % self.status
1091
1092
1093 if cite[-1] != '.':
1094 cite = cite + '.'
1095
1096
1097 return cite
1098
1099
1100
1102 """Bibliography container."""
1103
1104 type = "journal"
1105 author = "Bieri, M., d'Auvergne, E. J. and Gooley, P. R."
1106 author2 = [["Michael", "Bieri", "M.", ""], ["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1107 title = "relaxGUI: a new software for fast and simple NMR relaxation data analysis and calculation of ps-ns and micro-s motion of proteins"
1108 journal = "J. Biomol. NMR"
1109 journal_full = "Journal of Biomolecular NMR"
1110 abstract = "Investigation of protein dynamics on the ps-ns and mus-ms timeframes provides detailed insight into the mechanisms of enzymes and the binding properties of proteins. Nuclear magnetic resonance (NMR) is an excellent tool for studying protein dynamics at atomic resolution. Analysis of relaxation data using model-free analysis can be a tedious and time consuming process, which requires good knowledge of scripting procedures. The software relaxGUI was developed for fast and simple model-free analysis and is fully integrated into the software package relax. It is written in Python and uses wxPython to build the graphical user interface (GUI) for maximum performance and multi-platform use. This software allows the analysis of NMR relaxation data with ease and the generation of publication quality graphs as well as color coded images of molecular structures. The interface is designed for simple data analysis and management. The software was tested and validated against the command line version of relax."
1111 authoraddress = "Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Victoria 3010, Australia."
1112 doi = "10.1007/s10858-011-9509-1"
1113 pubmed_id = 21618018
1114 status = "published"
1115 year = 2011
1116
1117
1118
1120 """Bibliography container."""
1121
1122 type = "journal"
1123 author = "Clore, G. M. and Szabo, A. and Bax, A. and Kay, L. E. and Driscoll, P. C. and Gronenborn, A. M."
1124 title = "Deviations from the simple 2-parameter model-free approach to the interpretation of N-15 nuclear magnetic-relaxation of proteins"
1125 journal = "J. Am. Chem. Soc."
1126 journal_full = "Journal of the American Chemical Society"
1127 volume = "112"
1128 number = "12"
1129 pages = "4989-4991"
1130 address = "1155 16th St, NW, Washington, DC 20036"
1131 sourceid = "ISI:A1990DH27700070"
1132 status = "published"
1133 year = 1990
1134
1135
1136
1138 """Bibliography container."""
1139
1140 type = "thesis"
1141 author = "d'Auvergne, E. J."
1142 author2 = [["Edward", "d'Auvergne", "E.", "J."]]
1143 title = "Protein dynamics: a study of the model-free analysis of NMR relaxation data."
1144 school = "Biochemistry and Molecular Biology, University of Melbourne."
1145 url = "http://eprints.infodiv.unimelb.edu.au/archive/00002799/"
1146 status = "published"
1147 year = 2006
1148
1149
1150
1152 """Bibliography container."""
1153
1154 type = "journal"
1155 author = "d'Auvergne, E. J. and Gooley, P. R."
1156 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1157 title = "The use of model selection in the model-free analysis of protein dynamics."
1158 journal = "J. Biomol. NMR"
1159 journal_full = "Journal of Biomolecular NMR"
1160 volume = "25"
1161 number = "1"
1162 pages = "25-39"
1163 abstract = "Model-free analysis of NMR relaxation data, which is widely used for the study of protein dynamics, consists of the separation of the global rotational diffusion from internal motions relative to the diffusion frame and the description of these internal motions by amplitude and timescale. Five model-free models exist, each of which describes a different type of motion. Model-free analysis requires the selection of the model which best describes the dynamics of the NH bond. It will be demonstrated that the model selection technique currently used has two significant flaws, under-fitting, and not selecting a model when one ought to be selected. Under-fitting breaks the principle of parsimony causing bias in the final model-free results, visible as an overestimation of S2 and an underestimation of taue and Rex. As a consequence the protein falsely appears to be more rigid than it actually is. Model selection has been extensively developed in other fields. The techniques known as Akaike's Information Criteria (AIC), small sample size corrected AIC (AICc), Bayesian Information Criteria (BIC), bootstrap methods, and cross-validation will be compared to the currently used technique. To analyse the variety of techniques, synthetic noisy data covering all model-free motions was created. The data consists of two types of three-dimensional grid, the Rex grids covering single motions with chemical exchange [S2,taue,Rex], and the Double Motion grids covering two internal motions [S f 2,S s 2,tau s ]. The conclusion of the comparison is that for accurate model-free results, AIC model selection is essential. As the method neither under, nor over-fits, AIC is the best tool for applying Occam's razor and has the additional benefits of simplifying and speeding up model-free analysis."
1164 authoraddress = "Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Victoria 3010, Australia."
1165 keywords = "Amines ; Diffusion ; *Models, Molecular ; Motion ; Nuclear Magnetic Resonance, Biomolecular/*methods ; Proteins/*chemistry ; Research Support, Non-U.S. Gov't ; Rotation"
1166 doi = "10.1023/A:1021902006114"
1167 pubmed_id = 12566997
1168 status = "published"
1169 year = 2003
1170
1171
1172
1174 """Bibliography container."""
1175
1176 type = "journal"
1177 author = "d'Auvergne, E. J. and Gooley, P. R."
1178 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1179 title = "Model-free model elimination: A new step in the model-free dynamic analysis of NMR relaxation data."
1180 journal = "J. Biomol. NMR"
1181 journal_full = "Journal of Biomolecular NMR"
1182 volume = "35"
1183 number = "2"
1184 pages = "117-135"
1185 abstract = "Model-free analysis is a technique commonly used within the field of NMR spectroscopy to extract atomic resolution, interpretable dynamic information on multiple timescales from the R (1), R (2), and steady state NOE. Model-free approaches employ two disparate areas of data analysis, the discipline of mathematical optimisation, specifically the minimisation of a chi(2) function, and the statistical field of model selection. By searching through a large number of model-free minimisations, which were setup using synthetic relaxation data whereby the true underlying dynamics is known, certain model-free models have been identified to, at times, fail. This has been characterised as either the internal correlation times, tau( e ), tau( f ), or tau( s ), or the global correlation time parameter, local tau( m ), heading towards infinity, the result being that the final parameter values are far from the true values. In a number of cases the minimised chi(2) value of the failed model is significantly lower than that of all other models and, hence, will be the model which is chosen by model selection techniques. If these models are not removed prior to model selection the final model-free results could be far from the truth. By implementing a series of empirical rules involving inequalities these models can be specifically isolated and removed. Model-free analysis should therefore consist of three distinct steps: model-free minimisation, model-free model elimination, and finally model-free model selection. Failure has also been identified to affect the individual Monte Carlo simulations used within error analysis. Each simulation involves an independent randomised relaxation data set and model-free minimisation, thus simulations suffer from exactly the same types of failure as model-free models. Therefore, to prevent these outliers from causing a significant overestimation of the errors the failed Monte Carlo simulations need to be culled prior to calculating the parameter standard deviations."
1186 authoraddress = "Department of Biochemistry and Molecular Biology, Bio21 Institute of Biotechnology and Molecular Science, University of Melbourne, Parkville, Victoria, 3010, Australia"
1187 doi = "10.1007/s10858-006-9007-z"
1188 pubmed_id = 16791734
1189 status = "published"
1190 year = 2006
1191
1192
1193
1195 """Bibliography container."""
1196
1197 type = "journal"
1198 author = "d'Auvergne, E. J. and Gooley, P. R."
1199 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1200 title = "Set theory formulation of the model-free problem and the diffusion seeded model-free paradigm."
1201 journal = "Mol. Biosys."
1202 journal_full = "Molecular BioSystems"
1203 volume = "3"
1204 number = "7"
1205 pages = "483-494"
1206 abstract = "Model-free analysis of NMR relaxation data, which describes the motion of individual atoms, is a problem intricately linked to the Brownian rotational diffusion of the macromolecule. The diffusion tensor parameters strongly influence the optimisation of the various model-free models and the subsequent model selection between them. Finding the optimal model of the dynamics of the system among the numerous diffusion and model-free models is hence quite complex. Using set theory, the entirety of this global problem has been encapsulated by the universal set Ll, and its resolution mathematically formulated as the universal solution Ll. Ever since the original Lipari and Szabo papers the model-free dynamics of a molecule has most often been solved by initially estimating the diffusion tensor. The model-free models which depend on the diffusion parameter values are then optimised and the best model is chosen to represent the dynamics of the residue. Finally, the global model of all diffusion and model-free parameters is optimised. These steps are repeated until convergence. For simplicity this approach to Ll will be labelled the diffusion seeded model-free paradigm. Although this technique suffers from a number of problems many have been solved. All aspects of the diffusion seeded paradigm and its consequences, together with a few alternatives to the paradigm, will be reviewed through the use of set notation."
1207 authoraddress = "Department of Biochemistry and Molecular Biology, Bio21 Institute of Biotechnology and Molecular Science, University of Melbourne, Parkville, Melbourne, Victoria 3010, Australia."
1208 keywords = "Magnetic Resonance Spectroscopy/*methods ; *Models, Theoretical ; Proteins/chemistry ; Thermodynamics"
1209 doi = "10.1039/b702202f"
1210 pubmed_id = 17579774
1211 status = "published"
1212 year = 2007
1213
1214
1215
1217 """Bibliography container."""
1218
1219 type = "journal"
1220 author = "d'Auvergne, E. J. and Gooley, P. R."
1221 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1222 title = "Optimisation of NMR dynamic models I. Minimisation algorithms and their performance within the model-free and Brownian rotational diffusion spaces."
1223 journal = "J. Biomol. NMR"
1224 journal_full = "Journal of Biomolecular NMR"
1225 volume = "40"
1226 number = "2"
1227 pages = "107-119"
1228 abstract = "The key to obtaining the model-free description of the dynamics of a macromolecule is the optimisation of the model-free and Brownian rotational diffusion parameters using the collected R (1), R (2) and steady-state NOE relaxation data. The problem of optimising the chi-squared value is often assumed to be trivial, however, the long chain of dependencies required for its calculation complicates the model-free chi-squared space. Convolutions are induced by the Lorentzian form of the spectral density functions, the linear recombinations of certain spectral density values to obtain the relaxation rates, the calculation of the NOE using the ratio of two of these rates, and finally the quadratic form of the chi-squared equation itself. Two major topological features of the model-free space complicate optimisation. The first is a long, shallow valley which commences at infinite correlation times and gradually approaches the minimum. The most severe convolution occurs for motions on two timescales in which the minimum is often located at the end of a long, deep, curved tunnel or multidimensional valley through the space. A large number of optimisation algorithms will be investigated and their performance compared to determine which techniques are suitable for use in model-free analysis. Local optimisation algorithms will be shown to be sufficient for minimisation not only within the model-free space but also for the minimisation of the Brownian rotational diffusion tensor. In addition the performance of the programs Modelfree and Dasha are investigated. A number of model-free optimisation failures were identified: the inability to slide along the limits, the singular matrix failure of the Levenberg-Marquardt minimisation algorithm, the low precision of both programs, and a bug in Modelfree. Significantly, the singular matrix failure of the Levenberg-Marquardt algorithm occurs when internal correlation times are undefined and is greatly amplified in model-free analysis by both the grid search and constraint algorithms. The program relax ( http://www.nmr-relax.com ) is also presented as a new software package designed for the analysis of macromolecular dynamics through the use of NMR relaxation data and which alleviates all of the problems inherent within model-free analysis."
1229 authoraddress = "Department of NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, D-37077, Goettingen, Germany"
1230 keywords = "*Algorithms ; Cytochromes c2/chemistry ; Diffusion ; *Models, Molecular ; Nuclear Magnetic Resonance, Biomolecular/*methods ; Rhodobacter capsulatus/chemistry ; *Rotation"
1231 doi = "10.1007/s10858-007-9214-2"
1232 pubmed_id = 18085410
1233 status = "published"
1234 year = 2008
1235
1236
1237
1239 """Bibliography container."""
1240
1241 type = "journal"
1242 author = "d'Auvergne, E. J. and Gooley, P. R."
1243 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1244 title = "Optimisation of NMR dynamic models II. A new methodology for the dual optimisation of the model-free parameters and the Brownian rotational diffusion tensor."
1245 journal = "J. Biomol. NMR"
1246 journal_full = "Journal of Biomolecular NMR"
1247 volume = "40"
1248 number = "2"
1249 pages = "121-133"
1250 abstract = "Finding the dynamics of an entire macromolecule is a complex problem as the model-free parameter values are intricately linked to the Brownian rotational diffusion of the molecule, mathematically through the autocorrelation function of the motion and statistically through model selection. The solution to this problem was formulated using set theory as an element of the universal set [formula: see text]-the union of all model-free spaces (d'Auvergne EJ and Gooley PR (2007) Mol. BioSyst. 3(7), 483-494). The current procedure commonly used to find the universal solution is to initially estimate the diffusion tensor parameters, to optimise the model-free parameters of numerous models, and then to choose the best model via model selection. The global model is then optimised and the procedure repeated until convergence. In this paper a new methodology is presented which takes a different approach to this diffusion seeded model-free paradigm. Rather than starting with the diffusion tensor this iterative protocol begins by optimising the model-free parameters in the absence of any global model parameters, selecting between all the model-free models, and finally optimising the diffusion tensor. The new model-free optimisation protocol will be validated using synthetic data from Schurr JM et al. (1994) J. Magn. Reson. B 105(3), 211-224 and the relaxation data of the bacteriorhodopsin (1-36)BR fragment from Orekhov VY (1999) J. Biomol. NMR 14(4), 345-356. To demonstrate the importance of this new procedure the NMR relaxation data of the Olfactory Marker Protein (OMP) of Gitti R et al. (2005) Biochem. 44(28), 9673-9679 is reanalysed. The result is that the dynamics for certain secondary structural elements is very different from those originally reported."
1251 authoraddress = "Department of NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, Goettingen, D-37077, Germany"
1252 keywords = "Algorithms ; Amides/chemistry ; Bacteriorhodopsins/chemistry ; Crystallography, X-Ray ; Diffusion ; *Models, Molecular ; Nuclear Magnetic Resonance, Biomolecular/*methods ; Olfactory Marker Protein/chemistry ; Peptide Fragments/chemistry ; Protein Structure, Secondary ; *Rotation"
1253 language = "eng"
1254 doi = "10.1007/s10858-007-9213-3"
1255 pubmed_id = 18085411
1256 status = "published"
1257 year = 2008
1258
1259
1260
1262 """Bibliography container."""
1263
1264 type = "journal"
1265 author = "Delaglio, F., Grzesiek, S., Vuister, G.W., Zhu, G., Pfeifer, J. and Bax, A."
1266 author2 = [["Frank", "Delaglio", "F.", None], ["Stephan", "Grzesiek", "S.", None], ["Geerten", "Vuister", "G.", "W."], ["Guang", "Zhu", "G.", None], ["John", "Pfeifer", "J.", None], ["Ad", "Bax", "A.", None]]
1267 title = "NMRPipe: a multidimensional spectral processing system based on UNIX pipes."
1268 journal = "J. Biomol. NMR"
1269 journal_full = "Journal of Biomolecular NMR"
1270 volume = "6"
1271 number = "3"
1272 pages = "277-293"
1273 abstract = "The NMRPipe system is a UNIX software environment of processing, graphics, and analysis tools designed to meet current routine and research-oriented multidimensional processing requirements, and to anticipate and accommodate future demands and developments. The system is based on UNIX pipes, which allow programs running simultaneously to exchange streams of data under user control. In an NMRPipe processing scheme, a stream of spectral data flows through a pipeline of processing programs, each of which performs one component of the overall scheme, such as Fourier transformation or linear prediction. Complete multidimensional processing schemes are constructed as simple UNIX shell scripts. The processing modules themselves maintain and exploit accurate records of data sizes, detection modes, and calibration information in all dimensions, so that schemes can be constructed without the need to explicitly define or anticipate data sizes or storage details of real and imaginary channels during processing. The asynchronous pipeline scheme provides other substantial advantages, including high flexibility, favorable processing speeds, choice of both all-in-memory and disk-bound processing, easy adaptation to different data formats, simpler software development and maintenance, and the ability to distribute processing tasks on multi-CPU computers and computer networks."
1274 authoraddress = "Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA."
1275 keywords = "Magnetic Resonance Spectroscopy/*instrumentation ; *Software"
1276 language = "eng"
1277 doi = "10.1007/BF00197809"
1278 pubmed_id = 8520220
1279 status = "published"
1280 year = 1995
1281
1282
1283
1285 """Bibliography container."""
1286
1287 author = "Goddard, T.D. and Kneller, D.G."
1288 author2 = [["Tom", "Goddard", "T.", "D."], ["Donald", "Kneller", "D.", "G."]]
1289 journal = "University of California, San Francisco."
1290 title = "Sparky 3."
1291 status = "unpublished"
1292 type = "internet"
1293
1294
1295
1297 """Bibliography container."""
1298
1299 type = "journal"
1300 author = "Lipari, G. and Szabo, A."
1301 title = "Model-free approach to the interpretation of nuclear magnetic-resonance relaxation in macromolecules I. Theory and range of validity"
1302 journal = "J. Am. Chem. Soc."
1303 journal_full = "Journal of the American Chemical Society"
1304 volume = "104"
1305 number = "17"
1306 pages = "4546-4559"
1307 authoraddress = "NIADDKD,Chem Phys Lab,Bethesda,MD 20205."
1308 sourceid = "ISI:A1982PC82900009"
1309 status = "published"
1310 year = 1982
1311
1312
1313
1315 """Bibliography container."""
1316
1317 type = "journal"
1318 author = "Lipari, G. and Szabo, A."
1319 title = "Model-free approach to the interpretation of nuclear magnetic-resonance relaxation in macromolecules II. Analysis of experimental results"
1320 journal = "J. Am. Chem. Soc."
1321 journal_full = "Journal of the American Chemical Society"
1322 volume = "104"
1323 number = "17"
1324 pages = "4559-4570"
1325 abstract = "For pt.I see ibid., vol.104, p.4546 (1982). In the preceding paper it has been shown that the unique dynamic information on fast internal motions in an NMR relaxation experiment on macromolecules in solution is specified by a generalized order parameter, S , and an effective correlation time, tau /sub e/. The authors now deal with the extraction and interpretation of this information. The procedure used to obtain S /sup 2/ and tau /sub e/ from experimental data by using a least-squares method and, in certain favorable circumstances, by using an analytical formula is described. A variety of experiments are then analyzed to yield information on the time scale and spatial restriction of internal motions of isoleucines in myoglobin, methionines in dihydrofolate reductase and myoglobin, a number of aliphatic residues in basic pancreatic trypsin inhibitor, and ethyl isocyanide bound to myoglobin, hemoglobin, and aliphatic side chains in three random-coil polymers. The numerical values of S /sup 2/ and tau /sub e / can be readily interpreted within the framework of a variety of models."
1326 authoraddress = "NIADDKD,Chem Phys Lab,Bethesda,MD 20205."
1327 sourceid = "ISI:A1982PC82900010"
1328 status = "published"
1329 year = 1982
1330