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22
23 """Module containing the introductory text container."""
24
25
26 import dep_check
27
28
29 if dep_check.ctypes_module:
30 import ctypes
31 if hasattr(ctypes, 'windll'):
32 import ctypes.wintypes
33 else:
34 ctypes = None
35 if dep_check.ctypes_structure_module:
36 from ctypes import Structure
37 else:
38 Structure = object
39 from os import environ, pathsep, waitpid
40 import platform
41 from re import search, sub
42 PIPE, Popen = None, None
43 if dep_check.subprocess_module:
44 from subprocess import PIPE, Popen
45 import sys
46 from textwrap import wrap
47
48
49 from status import Status; status = Status()
50 from version import repo_revision, repo_url, version, version_full
51
52
61
62
63
65 """A container storing information about relax."""
66
67
68 instance = None
69
71 """Create the program introduction text stings.
72
73 This class generates a container with the following objects:
74 - title: The program title 'relax'
75 - version: For example 'repository checkout' or '1.3.8'.
76 - desc: The short program description.
77 - copyright: A list of copyright statements.
78 - licence: Text pertaining to the licencing.
79 - errors: A list of import errors.
80 """
81
82
83 self.title = "relax"
84 self.version = version
85
86
87 self.website = "http://www.nmr-relax.com"
88
89
90 self.desc = "Molecular dynamics by NMR data analysis"
91
92
93 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."
94
95
96 self.copyright = []
97 self.copyright.append("Copyright (C) 2001-2006 Edward d'Auvergne")
98 self.copyright.append("Copyright (C) 2006-2016 the relax development team")
99 self.copyright_short = "Copyright (C) 2001-2016 the relax development team"
100
101
102 self.licence = "This is free software which you are welcome to modify and redistribute under the conditions of the GNU General Public License (GPL). This program, including all modules, is licensed under the GPL and comes with absolutely no warranty. For details type 'GPL' within the relax prompt."
103
104
105 self.errors = []
106 if not dep_check.C_module_exp_fn:
107 self.errors.append(dep_check.C_module_exp_fn_mesg)
108
109
110 self._setup_references()
111
112
113 - def __new__(self, *args, **kargs):
114 """Replacement function for implementing the singleton design pattern."""
115
116
117 if self.instance is None:
118 self.instance = object.__new__(self, *args, **kargs)
119
120
121 return self.instance
122
123
143
144
145 - def centre(self, string, width=100):
146 """Format the string to be centred to a certain number of spaces.
147
148 @param string: The string to centre.
149 @type string: str
150 @keyword width: The number of characters to centre to.
151 @type width: int
152 @return: The centred string with leading whitespace added.
153 @rtype: str
154 """
155
156
157 spaces = int((width - len(string)) / 2)
158
159
160 string = spaces * ' ' + string
161
162
163 return string
164
165
167 """Return a string representation of the file type.
168
169 @param path: The full path of the file to return information about.
170 @type path: str
171 @return: The single line file type information string.
172 @rtype: str
173 """
174
175
176 if Popen == None:
177 return ''
178
179
180 pipe = Popen('file --help', shell=True, stdout=PIPE, stderr=PIPE, close_fds=False)
181 err = pipe.stderr.readlines()
182 if err:
183 return ''
184
185
186 cmd = "file -b '%s'" % path
187
188
189 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
190 if not hasattr(ctypes, 'windll'):
191 waitpid(pipe.pid, 0)
192
193
194 data = pipe.stdout.readlines()
195
196
197 if data[0][:-1] == 'Mach-O universal binary with 3 architectures':
198
199 arch = [None, None, None]
200 for i in range(3):
201 row = data[i+1].split('\t')
202 arch[i] = row[1][:-1]
203 arch.sort()
204
205
206 if arch == ['Mach-O 64-bit executable x86_64', 'Mach-O executable i386', 'Mach-O executable ppc']:
207 file_type = '3-way exec (i386, ppc, x86_64)'
208 elif arch == ['Mach-O 64-bit bundle x86_64', 'Mach-O bundle i386', 'Mach-O bundle ppc']:
209 file_type = '3-way bundle (i386, ppc, x86_64)'
210 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']:
211 file_type = '3-way lib (i386, ppc, x86_64)'
212 elif arch == ['Mach-O 64-bit object x86_64', 'Mach-O object i386', 'Mach-O object ppc']:
213 file_type = '3-way obj (i386, ppc, x86_64)'
214 else:
215 file_type = '3-way %s' % arch
216
217
218 elif data[0][:-1] == 'Mach-O universal binary with 2 architectures':
219
220 arch = [None, None]
221 for i in range(2):
222 row = data[i+1].split('\t')
223 arch[i] = row[1][:-1]
224 arch.sort()
225
226
227 if arch == ['Mach-O executable i386', 'Mach-O executable ppc']:
228 file_type = '2-way exec (i386, ppc)'
229 elif arch == ['Mach-O bundle i386', 'Mach-O bundle ppc']:
230 file_type = '2-way bundle (i386, ppc)'
231 elif arch == ['Mach-O dynamically linked shared library i386', 'Mach-O dynamically linked shared library ppc']:
232 file_type = '2-way lib (i386, ppc)'
233 elif arch == ['Mach-O object i386', 'Mach-O object ppc']:
234 file_type = '2-way obj (i386, ppc)'
235 else:
236 file_type = '2-way %s' % arch
237
238
239 else:
240 file_type = data[0][:-1]
241 for i in range(1, len(data)):
242 row = data[i].split('\t')
243 arch[i] = row[1][:-1]
244 file_type += " %s" % arch
245
246
247 if file_type == None:
248 return ''
249 return file_type
250
251
275
276
277 - def intro_text(self):
278 """Create the introductory string for STDOUT printing.
279
280 This text is word-wrapped to a fixed width of 100 characters (or 80 on MS Windows).
281
282
283 @return: The introductory string.
284 @rtype: str
285 """
286
287
288 intro_string = '\n\n\n'
289
290
291 if version == 'repository checkout':
292 text = "%s %s r%s" % (self.title, self.version, repo_revision)
293 text2 = "%s" % (repo_url)
294 intro_string = intro_string + self.centre(text, status.text_width) + '\n' + self.centre(text2, status.text_width) + '\n\n'
295
296
297 else:
298 text = "%s %s" % (self.title, self.version)
299 intro_string = intro_string + self.centre(text, status.text_width) + '\n\n'
300
301
302 intro_string = intro_string + self.centre(self.desc, status.text_width) + '\n\n'
303
304
305 for i in range(len(self.copyright)):
306 intro_string = intro_string + self.centre(self.copyright[i], status.text_width) + '\n'
307 intro_string = intro_string + '\n'
308
309
310 for line in wrap(self.licence, status.text_width):
311 intro_string = intro_string + line + '\n'
312 intro_string = intro_string + '\n'
313
314
315 help = "Assistance in using the relax prompt and scripting interface can be accessed by typing 'help' within the prompt."
316 for line in wrap(help, status.text_width):
317 intro_string = intro_string + line + '\n'
318
319
320 for i in range(len(self.errors)):
321 intro_string = intro_string + '\n' + self.errors[i] + '\n'
322 intro_string = intro_string + '\n'
323
324
325 if hasattr(self, 'multi_processor_string'):
326 for line in wrap('Processor fabric: %s\n' % self.multi_processor_string, status.text_width):
327 intro_string = intro_string + line + '\n'
328
329
330 return intro_string
331
332
543
544
546 """Return a string for the processor name.
547
548 @return: The processor name, in much more detail than platform.processor().
549 @rtype: str
550 """
551
552
553 if Popen == None:
554 return ""
555
556
557 if not dep_check.subprocess_module:
558 return ""
559
560
561 system = platform.system()
562
563
564 if system == 'Linux':
565
566 cmd = "cat /proc/cpuinfo"
567
568
569 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
570 waitpid(pipe.pid, 0)
571
572
573 data = pipe.stdout.readlines()
574
575
576 for line in data:
577
578 if hasattr(line, 'decode'):
579 line = line.decode()
580
581
582 if search("model name", line):
583
584 name = sub(".*model name.*:", "", line, 1)
585 name = name.strip()
586
587
588 return name
589
590
591 if system == 'Windows' or system == 'Microsoft':
592 return platform.processor()
593
594
595 if system == 'Darwin':
596
597 environ['PATH'] += pathsep + '/usr/sbin'
598
599
600 cmd = "sysctl -n machdep.cpu.brand_string"
601
602
603 try:
604
605 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
606 waitpid(pipe.pid, 0)
607
608
609 data = pipe.stdout.readlines()
610
611
612 string = data[0]
613 if hasattr(string, 'decode'):
614 string = string.decode()
615
616
617
618 return string.strip()
619
620
621 except:
622 return ""
623
624
625 return ""
626
627
628 - def ram_info(self, format=" %-25s%s\n"):
629 """Return a string for printing to STDOUT with info from the Python packages used by relax.
630
631 @keyword format: The formatting string.
632 @type format: str
633 @return: The info string.
634 @rtype: str
635 """
636
637
638 if Popen == None:
639 return ''
640
641
642 text = ''
643
644
645 system = platform.system()
646
647
648 if system == 'Linux':
649 pipe = Popen('free -m', shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, close_fds=False)
650 free_lines = pipe.stdout.readlines()
651 if free_lines:
652
653 for line in free_lines:
654
655 row = line.split()
656
657
658 if row[0] == 'Mem:':
659 text += format % ("Total RAM size: ", row[1], "Mb")
660
661
662 if row[0] == 'Swap:':
663 text += format % ("Total swap size: ", row[1], "Mb")
664
665
666 if system == 'Windows' or system == 'Microsoft':
667
668 mem = MemoryStatusEx()
669
670
671 text += format % ("Total RAM size: ", mem.ullTotalPhys / 1024.**2, "Mb")
672
673
674 text += format % ("Total swap size: ", mem.ullTotalVirtual / 1024.**2, "Mb")
675
676
677 if system == 'Darwin':
678
679 environ['PATH'] += pathsep + '/usr/sbin'
680
681
682 cmd = "sysctl -n hw.physmem"
683 cmd2 = "sysctl -n hw.memsize"
684
685
686 try:
687
688 pipe = Popen(cmd, shell=True, stdout=PIPE, close_fds=False)
689 waitpid(pipe.pid, 0)
690
691
692 data = pipe.stdout.readlines()
693
694
695 pipe = Popen(cmd2, shell=True, stdout=PIPE, close_fds=False)
696 waitpid(pipe.pid, 0)
697
698
699 data2 = pipe.stdout.readlines()
700
701
702 ram = int(data[0].strip())
703 total = int(data2[0].strip())
704 swap = total - ram
705
706
707 text += format % ("Total RAM size: ", ram / 1024.**2, "Mb")
708
709
710 text += format % ("Total swap size: ", swap / 1024.**2, "Mb")
711
712
713 except:
714 pass
715
716
717 if not text:
718 text += format % ("Total RAM size: ", "?", "Mb")
719 text += format % ("Total swap size: ", "?", "Mb")
720
721
722 return text
723
724
774
775
777 """Return a string for printing to STDOUT with info about the current relax instance.
778
779 @return: The info string.
780 @rtype: str
781 """
782
783
784 text = ''
785
786
787 format = " %-25s%s\n"
788 format2 = " %-25s%s %s\n"
789
790
791 text = text + ("\nHardware information:\n")
792 if hasattr(platform, 'machine'):
793 text = text + (format % ("Machine: ", platform.machine()))
794 if hasattr(platform, 'processor'):
795 text = text + (format % ("Processor: ", platform.processor()))
796 text = text + (format % ("Processor name: ", self.processor_name()))
797 text = text + (format % ("Endianness: ", sys.byteorder))
798 text = text + self.ram_info(format=format2)
799
800
801 text = text + ("\nOperating system information:\n")
802 if hasattr(platform, 'system'):
803 text = text + (format % ("System: ", platform.system()))
804 if hasattr(platform, 'release'):
805 text = text + (format % ("Release: ", platform.release()))
806 if hasattr(platform, 'version'):
807 text = text + (format % ("Version: ", platform.version()))
808 if hasattr(platform, 'win32_ver') and platform.win32_ver()[0]:
809 text = text + (format % ("Win32 version: ", (platform.win32_ver()[0] + " " + platform.win32_ver()[1] + " " + platform.win32_ver()[2] + " " + platform.win32_ver()[3])))
810 if hasattr(platform, 'linux_distribution') and platform.linux_distribution()[0]:
811 text = text + (format % ("GNU/Linux version: ", (platform.linux_distribution()[0] + " " + platform.linux_distribution()[1] + " " + platform.linux_distribution()[2])))
812 if hasattr(platform, 'mac_ver') and platform.mac_ver()[0]:
813 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])))
814 if hasattr(platform, 'dist'):
815 text = text + (format % ("Distribution: ", (platform.dist()[0] + " " + platform.dist()[1] + " " + platform.dist()[2])))
816 if hasattr(platform, 'platform'):
817 text = text + (format % ("Full platform string: ", (platform.platform())))
818 if hasattr(ctypes, 'windll'):
819 text = text + (format % ("Windows architecture: ", (self.win_arch())))
820
821
822 text = text + ("\nPython information:\n")
823 if hasattr(platform, 'architecture'):
824 text = text + (format % ("Architecture: ", (platform.architecture()[0] + " " + platform.architecture()[1])))
825 if hasattr(platform, 'python_version'):
826 text = text + (format % ("Python version: ", platform.python_version()))
827 if hasattr(platform, 'python_branch'):
828 text = text + (format % ("Python branch: ", platform.python_branch()))
829 if hasattr(platform, 'python_build'):
830 text = text + ((format[:-1]+', %s\n') % ("Python build: ", platform.python_build()[0], platform.python_build()[1]))
831 if hasattr(platform, 'python_compiler'):
832 text = text + (format % ("Python compiler: ", platform.python_compiler()))
833 if hasattr(platform, 'libc_ver'):
834 text = text + (format % ("Libc version: ", (platform.libc_ver()[0] + " " + platform.libc_ver()[1])))
835 if hasattr(platform, 'python_implementation'):
836 text = text + (format % ("Python implementation: ", platform.python_implementation()))
837 if hasattr(platform, 'python_revision'):
838 text = text + (format % ("Python revision: ", platform.python_revision()))
839 if sys.executable:
840 text = text + (format % ("Python executable: ", sys.executable))
841 if hasattr(sys, 'flags'):
842 text = text + (format % ("Python flags: ", sys.flags))
843 if hasattr(sys, 'float_info'):
844 text = text + (format % ("Python float info: ", sys.float_info))
845 text = text + (format % ("Python module path: ", sys.path))
846
847
848 text = text + self.package_info()
849
850
851 text = text + "\nrelax information:\n"
852 text = text + (format % ("Version: ", version_full()))
853 if hasattr(self, "multi_processor_string"):
854 text += format % ("Processor fabric: ", self.multi_processor_string)
855
856
857 text = text + self.relax_module_info()
858
859
860 text = text + ("\n")
861
862
863 return text
864
865
867 """Determine the MS Windows architecture.
868
869 @return: The architecture string.
870 @rtype: str
871 """
872
873
874 if 'PROCESSOR_ARCHITEW6432' in environ:
875 arch = environ['PROCESSOR_ARCHITEW6432']
876
877
878 else:
879 arch = environ['PROCESSOR_ARCHITECTURE']
880
881
882 return arch
883
884
885
887 """Special object for obtaining hardware info in MS Windows."""
888
889 if hasattr(ctypes, 'windll'):
890 _fields_ = [
891 ('dwLength', ctypes.wintypes.DWORD),
892 ('dwMemoryLoad', ctypes.wintypes.DWORD),
893 ('ullTotalPhys', ctypes.c_ulonglong),
894 ('ullAvailPhys', ctypes.c_ulonglong),
895 ('ullTotalPageFile', ctypes.c_ulonglong),
896 ('ullAvailPageFile', ctypes.c_ulonglong),
897 ('ullTotalVirtual', ctypes.c_ulonglong),
898 ('ullAvailVirtual', ctypes.c_ulonglong),
899 ('ullExtendedVirtual', ctypes.c_ulonglong),
900 ]
901
903 """Set up the information and handle non MS Windows systems."""
904
905
906 if hasattr(ctypes, 'windll'):
907 self.dwLength = ctypes.sizeof(self)
908 ctypes.windll.kernel32.GlobalMemoryStatusEx(ctypes.byref(self))
909
910
911
913 """Reference base class."""
914
915
916 type = None
917 author = None
918 author2 = None
919 title = None
920 status = None
921 journal = None
922 journal_full = None
923 volume = None
924 number = None
925 doi = None
926 pubmed_id = None
927 url = None
928 pages = None
929 year = None
930
931
933 """Generate some variables on the fly.
934
935 This is only called for objects not found in the class.
936
937 @param name: The name of the object.
938 @type name: str
939 @raises AttributeError: If the object cannot be created.
940 @returns: The generated object.
941 @rtype: anything
942 """
943
944
945 if name in ['page_first', 'page_last']:
946
947 if not self.pages:
948 return None
949
950
951 vals = self.pages.split('-')
952
953
954 if len(vals) == 1:
955 return vals[0]
956
957
958 if name == 'page_first':
959 return vals[0]
960
961
962 if name == 'page_last':
963 return vals[1]
964
965 raise AttributeError(name)
966
967
968 - def cite_short(self, author=True, title=True, journal=True, volume=True, number=True, pages=True, year=True, doi=True, url=True, status=True):
969 """Compile a short citation.
970
971 The returned text will have the form of:
972
973 - 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.
974
975
976 @keyword author: The author flag.
977 @type author: bool
978 @keyword title: The title flag.
979 @type title: bool
980 @keyword journal: The journal flag.
981 @type journal: bool
982 @keyword volume: The volume flag.
983 @type volume: bool
984 @keyword number: The number flag.
985 @type number: bool
986 @keyword pages: The pages flag.
987 @type pages: bool
988 @keyword year: The year flag.
989 @type year: bool
990 @keyword doi: The doi flag.
991 @type doi: bool
992 @keyword url: The url flag.
993 @type url: bool
994 @keyword status: The status flag. This will only be shown if not 'published'.
995 @type status: bool
996 @return: The full citation.
997 @rtype: str
998 """
999
1000
1001 cite = ''
1002 if author and self.author and hasattr(self, 'author'):
1003 cite = cite + self.author
1004 if year and self.year and hasattr(self, 'year'):
1005 cite = cite + ' (' + repr(self.year) + ').'
1006 if title and self.title and hasattr(self, 'title'):
1007 cite = cite + ' ' + self.title
1008 if journal and self.journal and hasattr(self, 'journal'):
1009 cite = cite + ' ' + self.journal + ','
1010 if volume and self.volume and hasattr(self, 'volume'):
1011 cite = cite + ' ' + self.volume
1012 if number and self.number and hasattr(self, 'number'):
1013 cite = cite + '(' + self.number + '),'
1014 if pages and self.pages and hasattr(self, 'pages'):
1015 cite = cite + ' ' + self.pages
1016 if doi and self.doi and hasattr(self, 'doi'):
1017 cite = cite + ' (http://dx.doi.org/'+self.doi + ')'
1018 if url and self.url and hasattr(self, 'url'):
1019 cite = cite + ' (' + self.url + ')'
1020 if status and hasattr(self, 'status') and self.status != 'published':
1021 cite = cite + ' (' + self.status + ')'
1022
1023
1024 if cite[-1] != '.':
1025 cite = cite + '.'
1026
1027
1028 return cite
1029
1030
1031 - def cite_html(self, author=True, title=True, journal=True, volume=True, number=True, pages=True, year=True, doi=True, url=True, status=True):
1032 """Compile a citation for HTML display.
1033
1034 @keyword author: The author flag.
1035 @type author: bool
1036 @keyword title: The title flag.
1037 @type title: bool
1038 @keyword journal: The journal flag.
1039 @type journal: bool
1040 @keyword volume: The volume flag.
1041 @type volume: bool
1042 @keyword number: The number flag.
1043 @type number: bool
1044 @keyword pages: The pages flag.
1045 @type pages: bool
1046 @keyword year: The year flag.
1047 @type year: bool
1048 @keyword doi: The doi flag.
1049 @type doi: bool
1050 @keyword url: The url flag.
1051 @type url: bool
1052 @keyword status: The status flag. This will only be shown if not 'published'.
1053 @type status: bool
1054 @return: The full citation.
1055 @rtype: str
1056 """
1057
1058
1059 cite = ''
1060 if author and hasattr(self, 'author') and self.author:
1061 cite = cite + self.author
1062 if year and hasattr(self, 'year') and self.year:
1063 cite = cite + ' (' + repr(self.year) + ').'
1064 if title and hasattr(self, 'title') and self.title:
1065 cite = cite + ' ' + self.title
1066 if journal and hasattr(self, 'journal') and self.journal:
1067 cite = cite + ' <em>' + self.journal + '</em>,'
1068 if volume and hasattr(self, 'volume') and self.volume:
1069 cite = cite + ' <strong>' + self.volume + '</strong>'
1070 if number and hasattr(self, 'number') and self.number:
1071 cite = cite + '(' + self.number + '),'
1072 if pages and hasattr(self, 'pages') and self.pages:
1073 cite = cite + ' ' + self.pages
1074 if doi and hasattr(self, 'doi') and self.doi:
1075 cite = cite + ' (<a href="http://dx.doi.org/%s">abstract</a>)' % self.doi
1076 if url and hasattr(self, 'url') and self.url:
1077 cite = cite + ' (<a href="%s">url</a>)' % self.url
1078 if status and hasattr(self, 'status') and self.status != 'published':
1079 cite = cite + ' (<i>%s</i>)' % self.status
1080
1081
1082 if cite[-1] != '.':
1083 cite = cite + '.'
1084
1085
1086 return cite
1087
1088
1089
1091 """Bibliography container."""
1092
1093 type = "journal"
1094 author = "Bieri, M., d'Auvergne, E. J. and Gooley, P. R."
1095 author2 = [["Michael", "Bieri", "M.", ""], ["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1096 title = "relaxGUI: a new software for fast and simple NMR relaxation data analysis and calculation of ps-ns and micro-s motion of proteins"
1097 journal = "J. Biomol. NMR"
1098 journal_full = "Journal of Biomolecular NMR"
1099 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."
1100 authoraddress = "Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Victoria 3010, Australia."
1101 doi = "10.1007/s10858-011-9509-1"
1102 pubmed_id = 21618018
1103 status = "published"
1104 year = 2011
1105
1106
1107
1109 """Bibliography container."""
1110
1111 type = "journal"
1112 author = "Clore, G. M. and Szabo, A. and Bax, A. and Kay, L. E. and Driscoll, P. C. and Gronenborn, A. M."
1113 title = "Deviations from the simple 2-parameter model-free approach to the interpretation of N-15 nuclear magnetic-relaxation of proteins"
1114 journal = "J. Am. Chem. Soc."
1115 journal_full = "Journal of the American Chemical Society"
1116 volume = "112"
1117 number = "12"
1118 pages = "4989-4991"
1119 address = "1155 16th St, NW, Washington, DC 20036"
1120 sourceid = "ISI:A1990DH27700070"
1121 status = "published"
1122 year = 1990
1123
1124
1125
1127 """Bibliography container."""
1128
1129 type = "thesis"
1130 author = "d'Auvergne, E. J."
1131 author2 = [["Edward", "d'Auvergne", "E.", "J."]]
1132 title = "Protein dynamics: a study of the model-free analysis of NMR relaxation data."
1133 school = "Biochemistry and Molecular Biology, University of Melbourne."
1134 url = "http://eprints.infodiv.unimelb.edu.au/archive/00002799/"
1135 status = "published"
1136 year = 2006
1137
1138
1139
1141 """Bibliography container."""
1142
1143 type = "journal"
1144 author = "d'Auvergne, E. J. and Gooley, P. R."
1145 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1146 title = "The use of model selection in the model-free analysis of protein dynamics."
1147 journal = "J. Biomol. NMR"
1148 journal_full = "Journal of Biomolecular NMR"
1149 volume = "25"
1150 number = "1"
1151 pages = "25-39"
1152 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."
1153 authoraddress = "Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Victoria 3010, Australia."
1154 keywords = "Amines ; Diffusion ; *Models, Molecular ; Motion ; Nuclear Magnetic Resonance, Biomolecular/*methods ; Proteins/*chemistry ; Research Support, Non-U.S. Gov't ; Rotation"
1155 doi = "10.1023/A:1021902006114"
1156 pubmed_id = 12566997
1157 status = "published"
1158 year = 2003
1159
1160
1161
1163 """Bibliography container."""
1164
1165 type = "journal"
1166 author = "d'Auvergne, E. J. and Gooley, P. R."
1167 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1168 title = "Model-free model elimination: A new step in the model-free dynamic analysis of NMR relaxation data."
1169 journal = "J. Biomol. NMR"
1170 journal_full = "Journal of Biomolecular NMR"
1171 volume = "35"
1172 number = "2"
1173 pages = "117-135"
1174 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."
1175 authoraddress = "Department of Biochemistry and Molecular Biology, Bio21 Institute of Biotechnology and Molecular Science, University of Melbourne, Parkville, Victoria, 3010, Australia"
1176 doi = "10.1007/s10858-006-9007-z"
1177 pubmed_id = 16791734
1178 status = "published"
1179 year = 2006
1180
1181
1182
1184 """Bibliography container."""
1185
1186 type = "journal"
1187 author = "d'Auvergne, E. J. and Gooley, P. R."
1188 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1189 title = "Set theory formulation of the model-free problem and the diffusion seeded model-free paradigm."
1190 journal = "Mol. Biosys."
1191 journal_full = "Molecular BioSystems"
1192 volume = "3"
1193 number = "7"
1194 pages = "483-494"
1195 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."
1196 authoraddress = "Department of Biochemistry and Molecular Biology, Bio21 Institute of Biotechnology and Molecular Science, University of Melbourne, Parkville, Melbourne, Victoria 3010, Australia."
1197 keywords = "Magnetic Resonance Spectroscopy/*methods ; *Models, Theoretical ; Proteins/chemistry ; Thermodynamics"
1198 doi = "10.1039/b702202f"
1199 pubmed_id = 17579774
1200 status = "published"
1201 year = 2007
1202
1203
1204
1206 """Bibliography container."""
1207
1208 type = "journal"
1209 author = "d'Auvergne, E. J. and Gooley, P. R."
1210 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1211 title = "Optimisation of NMR dynamic models I. Minimisation algorithms and their performance within the model-free and Brownian rotational diffusion spaces."
1212 journal = "J. Biomol. NMR"
1213 journal_full = "Journal of Biomolecular NMR"
1214 volume = "40"
1215 number = "2"
1216 pages = "107-119"
1217 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."
1218 authoraddress = "Department of NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, D-37077, Goettingen, Germany"
1219 keywords = "*Algorithms ; Cytochromes c2/chemistry ; Diffusion ; *Models, Molecular ; Nuclear Magnetic Resonance, Biomolecular/*methods ; Rhodobacter capsulatus/chemistry ; *Rotation"
1220 doi = "10.1007/s10858-007-9214-2"
1221 pubmed_id = 18085410
1222 status = "published"
1223 year = 2008
1224
1225
1226
1228 """Bibliography container."""
1229
1230 type = "journal"
1231 author = "d'Auvergne, E. J. and Gooley, P. R."
1232 author2 = [["Edward", "d'Auvergne", "E.", "J."], ["Paul", "Gooley", "P.", "R."]]
1233 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."
1234 journal = "J. Biomol. NMR"
1235 journal_full = "Journal of Biomolecular NMR"
1236 volume = "40"
1237 number = "2"
1238 pages = "121-133"
1239 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."
1240 authoraddress = "Department of NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, Goettingen, D-37077, Germany"
1241 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"
1242 language = "eng"
1243 doi = "10.1007/s10858-007-9213-3"
1244 pubmed_id = 18085411
1245 status = "published"
1246 year = 2008
1247
1248
1249
1251 """Bibliography container."""
1252
1253 type = "journal"
1254 author = "Delaglio, F., Grzesiek, S., Vuister, G.W., Zhu, G., Pfeifer, J. and Bax, A."
1255 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]]
1256 title = "NMRPipe: a multidimensional spectral processing system based on UNIX pipes."
1257 journal = "J. Biomol. NMR"
1258 journal_full = "Journal of Biomolecular NMR"
1259 volume = "6"
1260 number = "3"
1261 pages = "277-293"
1262 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."
1263 authoraddress = "Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA."
1264 keywords = "Magnetic Resonance Spectroscopy/*instrumentation ; *Software"
1265 language = "eng"
1266 doi = "10.1007/BF00197809"
1267 pubmed_id = 8520220
1268 status = "published"
1269 year = 1995
1270
1271
1272
1274 """Bibliography container."""
1275
1276 author = "Goddard, T.D. and Kneller, D.G."
1277 author2 = [["Tom", "Goddard", "T.", "D."], ["Donald", "Kneller", "D.", "G."]]
1278 journal = "University of California, San Francisco."
1279 title = "Sparky 3."
1280 status = "unpublished"
1281 type = "internet"
1282
1283
1284
1286 """Bibliography container."""
1287
1288 type = "journal"
1289 author = "Lipari, G. and Szabo, A."
1290 title = "Model-free approach to the interpretation of nuclear magnetic-resonance relaxation in macromolecules I. Theory and range of validity"
1291 journal = "J. Am. Chem. Soc."
1292 journal_full = "Journal of the American Chemical Society"
1293 volume = "104"
1294 number = "17"
1295 pages = "4546-4559"
1296 authoraddress = "NIADDKD,Chem Phys Lab,Bethesda,MD 20205."
1297 sourceid = "ISI:A1982PC82900009"
1298 status = "published"
1299 year = 1982
1300
1301
1302
1304 """Bibliography container."""
1305
1306 type = "journal"
1307 author = "Lipari, G. and Szabo, A."
1308 title = "Model-free approach to the interpretation of nuclear magnetic-resonance relaxation in macromolecules II. Analysis of experimental results"
1309 journal = "J. Am. Chem. Soc."
1310 journal_full = "Journal of the American Chemical Society"
1311 volume = "104"
1312 number = "17"
1313 pages = "4559-4570"
1314 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."
1315 authoraddress = "NIADDKD,Chem Phys Lab,Bethesda,MD 20205."
1316 sourceid = "ISI:A1982PC82900010"
1317 status = "published"
1318 year = 1982
1319