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3 changed files
with
1080 additions
and
356 deletions
data-sets/genes.txt
0 → 100644
1 | +TGF-beta1 | ||
2 | +Insulin-like growth factor-1 | ||
3 | +CD86 | ||
4 | +HS6ST2 | ||
5 | +Snail1/2 | ||
6 | +interferon-gamma | ||
7 | +Focal adhesion kinase | ||
8 | +protease-activated receptor-1 | ||
9 | +mPAP | ||
10 | +nuclear factor erythroid 2-related factor 2 | ||
11 | +NF-kB | ||
12 | +Fos | ||
13 | +HDAC6 | ||
14 | +CD90 | ||
15 | +interleukin-12p40 | ||
16 | +Mitogen-activated protein kinase-activated protein kinase-2 | ||
17 | +collagen-1, ET-1 | ||
18 | +smooth muscle a-actin | ||
19 | +caspase-3 | ||
20 | +Angiotensin II | ||
21 | +IL-23 | ||
22 | +HDAC | ||
23 | +matriptase | ||
24 | +CD124 | ||
25 | +Keap1 | ||
26 | +transforming growth factor-beta-1 | ||
27 | +TGF-a | ||
28 | +Cysteine-rich protein 1 | ||
29 | +glycogen synthase kinase-3beta | ||
30 | +Cartilage oligomeric matrix protein | ||
31 | +TGFb2 | ||
32 | +miR-338* | ||
33 | +C3aR | ||
34 | +E -cadherin | ||
35 | +TGF beta 1 | ||
36 | +miR-200b | ||
37 | +pVHL | ||
38 | +Activin | ||
39 | +BMP-8B | ||
40 | +Foxp-3 | ||
41 | +HAI-1 | ||
42 | +IL-1b | ||
43 | +WNT5A | ||
44 | +AQP5 | ||
45 | +MT1 | ||
46 | +stromal-cell-derived factor-1 | ||
47 | +tgfb2 | ||
48 | +monocyte chemotactic protein-1 | ||
49 | +SpA | ||
50 | +IL-1 beta, -2, -4, -5, -6, -8, -10, -17 | ||
51 | +insulin-like growth factor-I | ||
52 | +ECSOD | ||
53 | +SPARC | ||
54 | +E-CAD | ||
55 | +TGF-b(1) | ||
56 | +il17a | ||
57 | +COL1A2 | ||
58 | +TGF-b-1 | ||
59 | +Atg4b | ||
60 | +ET-B | ||
61 | +KGF | ||
62 | +NOX-4 | ||
63 | +col1a2 | ||
64 | +pten | ||
65 | +miR-26a | ||
66 | +S1PL | ||
67 | +alpha-smooth muscle actin | ||
68 | +Glut-1 and glucokinase | ||
69 | +TGFbeta1 | ||
70 | +Transforming growth factor beta1 | ||
71 | +CCl4 | ||
72 | +transforming growth factor -b1 | ||
73 | +serum amyloid P | ||
74 | +miR-338 | ||
75 | +Bone morphogenetic protein 3 | ||
76 | +COL3A1 | ||
77 | +ALK5 | ||
78 | +PSPH | ||
79 | +HO-1 | ||
80 | +histone deacetylase 4 | ||
81 | +tsp1 | ||
82 | +FGF-10 | ||
83 | +interferon (IFN)-gamma | ||
84 | +E-Cad | ||
85 | +Protease nexin-1 | ||
86 | +ILK | ||
87 | +TGF-b receptor II | ||
88 | +TGFB | ||
89 | +insulin promoting factor-1 | ||
90 | +EGFR | ||
91 | +LXRa | ||
92 | +Interleukin 17A | ||
93 | +MiR-185 | ||
94 | +Semaphorin-7A | ||
95 | +SPHK1 | ||
96 | +transforming growth factor-b(1) | ||
97 | +K-ras | ||
98 | +p27 | ||
99 | +pai1 | ||
100 | +Mmp19 | ||
101 | +Col1A1 | ||
102 | +Follistatin-like 1 | ||
103 | +Serine Protease | ||
104 | +Smad3 and 4 | ||
105 | +Bone morphogenetic protein | ||
106 | +PDGF-B | ||
107 | +BMP-4 | ||
108 | +min(-1 | ||
109 | +ORP150 | ||
110 | +bmp1 | ||
111 | +RAGE | ||
112 | +SGPL1 | ||
113 | +SOCS-1 | ||
114 | +tagln2 | ||
115 | +MMP-12 | ||
116 | +DRB1 | ||
117 | +MyD88 | ||
118 | +STC1 | ||
119 | +150-kDa oxygen-regulated protein | ||
120 | +MMP-9 | ||
121 | +IP10 | ||
122 | +terminal deoxynucleotidyl transferase | ||
123 | +TGF-beta 1 | ||
124 | +NADPH oxidase-4 | ||
125 | +transforming growth factor-beta | ||
126 | +Prostaglandin A(1) | ||
127 | +p70 | ||
128 | +IgG1 | ||
129 | +N-acetyl-l-cysteine | ||
130 | +Tgfbr1/2 | ||
131 | +HGFA | ||
132 | +DNMT1 | ||
133 | +nuclear factor kappa B | ||
134 | +plasminogen activator inhibitor 1 | ||
135 | +S1P | ||
136 | +angiopoietin-2 | ||
137 | +KCa3.1 | ||
138 | +ENA-78 | ||
139 | +WNT3a | ||
140 | +miR-134 | ||
141 | +P53 | ||
142 | +matrix metalloproteinase (MMP) -2 | ||
143 | +vimentin | ||
144 | +MMP-2 | ||
145 | +endoglin | ||
146 | +tumor necrosis factor superfamily protein 14 | ||
147 | +Transforming Growth Factor Beta 1 | ||
148 | +Cebpb | ||
149 | +Mknk2 | ||
150 | +SDF-1-TR1 | ||
151 | +Endothelin-1 | ||
152 | +HFL-1 | ||
153 | +MIG | ||
154 | +TGF-beta receptors type I and II (T beta R-I and T beta R-II | ||
155 | +IL-8 | ||
156 | +YY-1 | ||
157 | +MMP1 | ||
158 | +interferon gamma (IFN-y | ||
159 | +MIP-1 alpha | ||
160 | +IL-4RA | ||
161 | +HS6ST1 | ||
162 | +BMPR2 | ||
163 | +sL1 | ||
164 | +transforming growth factor-alpha | ||
165 | +Transgelin | ||
166 | +TGF-beta 3 | ||
167 | +lox | ||
168 | +CTGF | ||
169 | +MCP-1 | ||
170 | +tumor necrosis factor | ||
171 | +MT3 | ||
172 | +cytosolic phospholipase A(2) | ||
173 | +Thymic stromal lymphopoietin | ||
174 | +phosphoglycerate dehydrogenase | ||
175 | +Bax | ||
176 | +Caveolin-1 (cav-1 | ||
177 | +UCHL5 | ||
178 | +TIMP-1 | ||
179 | +JunD | ||
180 | +Transforming growth factor (TGF)-b1 | ||
181 | +MicroRNA (miR)-221 | ||
182 | +miR-424 | ||
183 | +YAP | ||
184 | +Aortic carboxypeptidase-like protein | ||
185 | +Microsomal prostaglandin E synthase-1 | ||
186 | +b2 -adrenoceptors | ||
187 | +YKL-40 | ||
188 | +VE-cadherin | ||
189 | +transforming growth factor-beta(1) | ||
190 | +PML | ||
191 | +CXCL12 | ||
192 | +VEGF-C | ||
193 | +LMP1 | ||
194 | +miR-30a | ||
195 | +insulin-like growth factor)-1 | ||
196 | +histone deacetylase | ||
197 | +b-catenin | ||
198 | +RANTES | ||
199 | +latent membrane protein (LMP) 1 | ||
200 | +Itgb6 | ||
201 | +CXCL1 | ||
202 | +VEGFR-3 | ||
203 | +glucokinase | ||
204 | +TNFSF14 | ||
205 | +matrix metalloproteinase-3 | ||
206 | +TNFa | ||
207 | +renin | ||
208 | +VCAM1 | ||
209 | +GATA-6 | ||
210 | +Transforming growth factor-b(1 | ||
211 | +angiotensinogen | ||
212 | +Smad7 | ||
213 | +cC1q-R | ||
214 | +IL-1R | ||
215 | +tgfbr1/2 | ||
216 | +FoxP3 | ||
217 | +a-SMA | ||
218 | +CCL12 | ||
219 | +CCN2 | ||
220 | +PDE1A | ||
221 | +PAR-2 | ||
222 | +serum albumin (HSA)-thioredoxin 1 | ||
223 | +tissue inhibitor of metalloproteinase (TIMP)-1 | ||
224 | +HIF-1a | ||
225 | +FRNK | ||
226 | +TGF-alpha | ||
227 | +miR-200c | ||
228 | +poly-ADP ribose polymerase | ||
229 | +Spiruchostatin A | ||
230 | +Sgpl1 | ||
231 | +FXa | ||
232 | +Extracellular superoxide dismutase | ||
233 | +Tgf-b | ||
234 | +Tb4 | ||
235 | +CUX1 | ||
236 | +gC1q-R | ||
237 | +FGF10 | ||
238 | +Tpo | ||
239 | +AKT | ||
240 | +insulin-like growth factor-1 | ||
241 | +IL-4R alpha | ||
242 | +IFN-gamma | ||
243 | +JAK2 | ||
244 | +MMP-7 | ||
245 | +smad3 | ||
246 | +NOX4 | ||
247 | +Bach1 | ||
248 | +caspase-9 | ||
249 | +transforming growth factor b1 | ||
250 | +interleukin-6 | ||
251 | +Serpin B3 | ||
252 | +Pentraxin-2 | ||
253 | +T-cell lymphoma invasion and metastasis 1 | ||
254 | +GR | ||
255 | +prostaglandin F (PGF) receptor | ||
256 | +serine protease | ||
257 | +MMP-19 | ||
258 | +SMAD 3 | ||
259 | +MMP7 | ||
260 | +p62 | ||
261 | +connective tissue growth factor | ||
262 | +Renin | ||
263 | +discoidin domain receptor 2 | ||
264 | +mothers against decapentaplegic homolog 3 | ||
265 | +IL-1RA | ||
266 | +Trx | ||
267 | +HAI-2 | ||
268 | +WNT1-inducible signaling pathway protein 1 | ||
269 | +Ubiquitin carboxyl-terminal hydrolase-L5 | ||
270 | +CC16 | ||
271 | +interleukin-10 | ||
272 | +LTBP-1 | ||
273 | +EDA | ||
274 | +BMP-5 | ||
275 | +miR-154 | ||
276 | +CD80 | ||
277 | +p110 | ||
278 | +LTBP1 and 2 | ||
279 | +periostin | ||
280 | +EP2 | ||
281 | +TGF-beta | ||
282 | +C3a | ||
283 | +H2O2 and tumor necrosis factor alpha | ||
284 | +CD1 | ||
285 | +Mir-154 | ||
286 | +cyclooxygenase-2 | ||
287 | +LTBP] 1, 2, and 4 | ||
288 | +matrix metalloproteinase-14(+)/matrix metalloproteinase-2(+) myofibroblasts | ||
289 | +Chop | ||
290 | +TGF-beta(1) | ||
291 | +MK2 | ||
292 | +SMO | ||
293 | +PPARy | ||
294 | +insulin-like growth factor binding protein-3 | ||
295 | +TGF-beta(1), collagen type Ialpha1 | ||
296 | +hyaluronan synthase 2 | ||
297 | +endothelin type A receptors | ||
298 | +TNF-alpha | ||
299 | +TNC | ||
300 | +transforming growth factor (TGF)-beta 1 | ||
301 | +Enhancer of zeste homolog 2 | ||
302 | +Snail | ||
303 | +IL-1Ra | ||
304 | +MMP-1 | ||
305 | +interleukin-8 | ||
306 | +PGA(1) | ||
307 | +lymphotoxin beta receptor | ||
308 | +TGF-beta 2 | ||
309 | +Lefty A | ||
310 | +Sulf1 | ||
311 | +serine hydroxymethyltransferase 2 | ||
312 | +IFN-y | ||
313 | +LOX | ||
314 | +Transforming growth factor (TGF)-b | ||
315 | +TGF- b | ||
316 | +NOS | ||
317 | +Smad 7 | ||
318 | +hypoxia-inducible factor 1a | ||
319 | +Transglutaminase 2 | ||
320 | +mTORC2 | ||
321 | +C5a | ||
322 | +annexin V | ||
323 | +thyroid transcription factor (TTF)-1 | ||
324 | +CXCL9 | ||
325 | +transforming growth factor-beta 1 | ||
326 | +Vascular endothelial growth factor | ||
327 | +beclin-1 | ||
328 | +extracellular signal-regulated kinase (ERK)1/2 | ||
329 | +TGF-{beta}1 | ||
330 | +Caspase-3 | ||
331 | +CCN5 | ||
332 | +IL-17A | ||
333 | +ARPC2 | ||
334 | +matrix metalloproteinase 9 | ||
335 | +p16 | ||
336 | +glucagon like peptide-1 | ||
337 | +L1-CAM | ||
338 | +TGF -b | ||
339 | +fibroblast growth factor-1 | ||
340 | +TGFbeta | ||
341 | +IGFBP-1 | ||
342 | +ubiquitin carboxyl-terminal hydrolase-L5 | ||
343 | +SMAD3 | ||
344 | +glucocorticoid receptor | ||
345 | +Transforming growth factor b1 | ||
346 | +TNF)-alpha | ||
347 | +IL18 | ||
348 | +TOB2 | ||
349 | +TbRII | ||
350 | +WNT7B | ||
351 | +SMAD-3 | ||
352 | +HLA-A, -B, -DRB1, tumor necrosis factor alpha | ||
353 | +TF | ||
354 | +miR-3107 | ||
355 | +zonula occludens-1 | ||
356 | +Nuclear factor-erythroid-related factor 2 | ||
357 | +Sulf2 | ||
358 | +ADAMTS9 | ||
359 | +Surfactant Protein-C | ||
360 | +TNFalpha | ||
361 | +IL10 | ||
362 | +actin related protein 2/3 complex, subunit 2 | ||
363 | +secreted protein acidic and rich in cysteine | ||
364 | +Krebs Von Den Lungen-6 | ||
365 | +Il-1b | ||
366 | +HNP-1 | ||
367 | +Fstl1 | ||
368 | +miR-382 | ||
369 | +matrix metalloproteinase (MMP)-2 and -9 | ||
370 | +SphK1/2 | ||
371 | +IQGAP1 | ||
372 | +SNAI2 | ||
373 | +Rictor | ||
374 | +SHH | ||
375 | +ACTA2 | ||
376 | +SIRT1 | ||
377 | +Sema 7a-CD4 | ||
378 | +WNT10A | ||
379 | +Insulin-like growth factor binding protein-3 | ||
380 | +FSP-1 | ||
381 | +poly(ADP-ribose) polymerase | ||
382 | +LRP5 | ||
383 | +MMP-3 | ||
384 | +Interleukin (IL) 8 | ||
385 | +Wilms' tumor 1 | ||
386 | +Fibrillin-2 | ||
387 | +tnf-alpha | ||
388 | +aSMA | ||
389 | +IL-9 | ||
390 | +HLA-A | ||
391 | +cartilage oligomeric matrix protein | ||
392 | +thrombin | ||
393 | +tumor necrosis factor alpha | ||
394 | +beta-catenin | ||
395 | +FAK | ||
396 | +Th1 | ||
397 | +YY1 | ||
398 | +NFkB | ||
399 | +Lox | ||
400 | +Caveolin-1 | ||
401 | +Membrane-type (MT)-MMPs | ||
402 | +Galectin-3 | ||
403 | +smoothened | ||
404 | +Smad3 | ||
405 | +claudins-1 and -3 | ||
406 | +ERK1/2 | ||
407 | +Bone Morphogenic Protein Receptor 2 | ||
408 | +acyl-CoA oxidase 1 | ||
409 | +serpine1 | ||
410 | +VASH-2 | ||
411 | +miR-326 | ||
412 | +TGFB1 | ||
413 | +phosphoinositide 3-kinase | ||
414 | +bone morphogenetic protein | ||
415 | +interleukin (IL)-13 | ||
416 | +c-Myc | ||
417 | +TGF-b3 | ||
418 | +NFATc2 | ||
419 | +TIMP-2 | ||
420 | +SMAD2 | ||
421 | +CD25 | ||
422 | +Smad2/3 | ||
423 | +V-ATPase | ||
424 | +LMP-1 | ||
425 | +C1q receptor | ||
426 | +glutathione peroxidase 1 | ||
427 | +C5a receptor | ||
428 | +IL-1 alpha, -1R, -1RA, -2, -4, -4R alpha, -6, -10 | ||
429 | +platelet-derived growth factor isoforms (PDGF) A and B | ||
430 | +IL-1-beta | ||
431 | +Transforming growth factor-beta1 | ||
432 | +galectin-3 | ||
433 | +PAR1 | ||
434 | +SIRT7 | ||
435 | +p65 | ||
436 | +Transforming growth factor beta | ||
437 | +cPLA(2) | ||
438 | +desmin | ||
439 | +Histone deacetylase 6 | ||
440 | +EMT | ||
441 | +transforming growth factor (TGF)-beta1 | ||
442 | +IGFBP-1 and -2 | ||
443 | +TGFBR-2 | ||
444 | +transforming growth factor beta | ||
445 | +HSP90 | ||
446 | +miR-29b | ||
447 | +CD248 | ||
448 | +PPARbeta | ||
449 | +follistatin | ||
450 | +TGF-beta(1 | ||
451 | +Janus kinase type 2 | ||
452 | +A-myb | ||
453 | +nuclear factor E2-related factor 2 | ||
454 | +Heat shock protein (HSP) 47 | ||
455 | +VCAM-1 | ||
456 | +mmu-miR-326 | ||
457 | +PARP | ||
458 | +LXA4 receptor | ||
459 | +G-CSF | ||
460 | +transforming-growth factor beta 1 | ||
461 | +Matriptase | ||
462 | +MiR-5100 | ||
463 | +IL-6 | ||
464 | +VEGFR | ||
465 | +CXCL-9 | ||
466 | +Rpn6 | ||
467 | +IL-10 | ||
468 | +alpha1 type I collagen | ||
469 | +Smad4 | ||
470 | +matrix metalloproteinase-9 | ||
471 | +PHLPP | ||
472 | +Tumor necrosis factor-alpha | ||
473 | +thyroid transcription factor-1 | ||
474 | +insulin | ||
475 | +Ang-2 | ||
476 | +basic FGF | ||
477 | +tagln | ||
478 | +TGFbeta(1) | ||
479 | +b-FGF | ||
480 | +miR-210 | ||
481 | +Lrp5 and 6 | ||
482 | +PDGF-b | ||
483 | +FN1 | ||
484 | +HMGA2 | ||
485 | +LYCAT | ||
486 | +Tumor necrosis factor a | ||
487 | +IL-2 | ||
488 | +IL1-b | ||
489 | +PAI-1 | ||
490 | +VEGFR-2 | ||
491 | +igf1 | ||
492 | +Ho-1 | ||
493 | +aquaporin-5 | ||
494 | +VEGF receptor-2 | ||
495 | +COMP | ||
496 | +c-jun | ||
497 | +mir-155 | ||
498 | +megakaryoblastic leukemia 1 | ||
499 | +Kca3.1 | ||
500 | +tissue inhibitors of metalloproteinases-1 | ||
501 | +Secreted protein acidic and rich in cysteine | ||
502 | +CD-1 | ||
503 | +Cyclin D1 | ||
504 | +tenascin C | ||
505 | +phosphoserine aminotransferase 1 | ||
506 | +Lin28B | ||
507 | +Gremlin | ||
508 | +tropomodulin 3 | ||
509 | +PIAS4 | ||
510 | +interleukin 10 | ||
511 | +epidermal growth factor receptor | ||
512 | +c-IAP2 | ||
513 | +fibroblast growth factor receptor 2 | ||
514 | +CRP1 | ||
515 | +Collagen Triple Helix Repeat-Containing-1 | ||
516 | +transforming growth factor-b1 | ||
517 | +PTX-2 | ||
518 | +CD11b | ||
519 | +IL-4 R alpha | ||
520 | +TG2 | ||
521 | +IGFBP-2 | ||
522 | +cytochrome b | ||
523 | +BLTR | ||
524 | +lysyl oxidase | ||
525 | +alpha smooth muscle actin | ||
526 | +UCH37 | ||
527 | +Receptor for advanced glycation end products | ||
528 | +IL-1 beta | ||
529 | +miR-376c | ||
530 | +miR-153 | ||
531 | +Smad2/3/4 | ||
532 | +LEF/TCF | ||
533 | +thymosin b4 | ||
534 | +plasminogen activator inhibitor-1 | ||
535 | +beta-galactosidase | ||
536 | +Stanniocalcin-1 | ||
537 | +THP-1 | ||
538 | +Egr-1 | ||
539 | +beta-gal | ||
540 | +PDGFR | ||
541 | +Transforming growth factor b-1 | ||
542 | +transforming growth factor beta 1 | ||
543 | +miR-410 | ||
544 | +TGF-b(1 | ||
545 | +focal adhesion kinase | ||
546 | +STAT3 | ||
547 | +Prostaglandin F(2alpha) receptor | ||
548 | +Nox-4 | ||
549 | +Toll-like receptor 9 | ||
550 | +CCL2 | ||
551 | +GM-CSF | ||
552 | +folate receptor beta | ||
553 | +Elk1 | ||
554 | +interleukin (IL)-1beta | ||
555 | +mTOR | ||
556 | +vascular cell adhesion molecule 1 | ||
557 | +E-cadherin | ||
558 | +PPARgamma | ||
559 | +Serpine1 | ||
560 | +PAI1 | ||
561 | +TIMP | ||
562 | +SFTPC | ||
563 | +VEGF and IL-12 | ||
564 | +LTBP 4 | ||
565 | +Nuclear factor erythroid 2-related factor 2 | ||
566 | +Jun NH2-terminal kinase | ||
567 | +FAK(Y397 | ||
568 | +IL-18 | ||
569 | +Transforming growth factor-b | ||
570 | +il-1b | ||
571 | +SphK | ||
572 | +DDR2 | ||
573 | +FOXF1 | ||
574 | +TIMP1 | ||
575 | +SHMT2 | ||
576 | +SOD3 | ||
577 | +TGFb1 | ||
578 | +FN | ||
579 | +TIMP2 | ||
580 | +FRbeta | ||
581 | +Interleukin 4 | ||
582 | +E-cad | ||
583 | +p38 | ||
584 | +VEGF-D | ||
585 | +Periostin | ||
586 | +Sp1 | ||
587 | +CC1q-R | ||
588 | +KL-6 | ||
589 | +ADAM19 | ||
590 | +miR-185 | ||
591 | +USP11 | ||
592 | +IL8 | ||
593 | +Akt2 | ||
594 | +BMPER | ||
595 | +IFN-gammaR | ||
596 | +Akt | ||
597 | +IL-1 | ||
598 | +hepatocyte growth factor | ||
599 | +MAPKAPK2 | ||
600 | +uncoupling protein 2 | ||
601 | +thrombospondin-1 | ||
602 | +serum response factor | ||
603 | +CD55 | ||
604 | +Gpx1 | ||
605 | +Id3 | ||
606 | +PAR-1 | ||
607 | +keratinocyte growth factor | ||
608 | +TIGAR | ||
609 | +NADPH oxidase 4 | ||
610 | +integrin-linked kinase | ||
611 | +interleukin-1 receptor antagonist protein | ||
612 | +PHGDH | ||
613 | +mPGES-1 | ||
614 | +matrix metalloproteinase 14 | ||
615 | +STIP1 | ||
616 | +CCN1 | ||
617 | +angiopoietin-1 | ||
618 | +CD44 | ||
619 | +TGF-b1 | ||
620 | +PN-1 | ||
621 | +BMP endothelial cell precursor-derived regulator | ||
622 | +MFG-E8 | ||
623 | +PPAR | ||
624 | +protein kinase B | ||
625 | +IGFBP-3 | ||
626 | +EMMPRIN | ||
627 | +cyclosporine A | ||
628 | +semaphorin-7A | ||
629 | +SNAI1 | ||
630 | +Pink1 | ||
631 | +PINK1 | ||
632 | +Bone morphogenetic protein-4 | ||
633 | +CBP | ||
634 | +IL-17 | ||
635 | +AT1 | ||
636 | +TGFBR2 | ||
637 | +N-acetyl-L-cysteine | ||
638 | +endothelin-1 | ||
639 | +smad-2 | ||
640 | +Interleukin (IL)-6 | ||
641 | +ET-1 | ||
642 | +AP-1 | ||
643 | +HDAC4 | ||
644 | +c-Fos | ||
645 | +HSP27 | ||
646 | +WISP1 | ||
647 | +Transforming growth factor beta 1 | ||
648 | +jag1 | ||
649 | +Nrf2 | ||
650 | +cyclooxygenase 2 | ||
651 | +smad6/7 | ||
652 | +WNT5a | ||
653 | +mir-154 | ||
654 | +SP-D | ||
655 | +Matrix metalloproteinase (MMP)-19 | ||
656 | +Vasohibin-2 | ||
657 | +caspase 3 | ||
658 | +Smad1/5 | ||
659 | +miR-200a | ||
660 | +TNF-a | ||
661 | +IGFBP-3 and -5 | ||
662 | +p53 | ||
663 | +Serpin B4 | ||
664 | +Transcription factor GATA-6 | ||
665 | +ACLP | ||
666 | +transgelin | ||
667 | +NADPH Oxidase 4 | ||
668 | +ZO-1 | ||
669 | +Cthrc1 | ||
670 | +VEGF-A | ||
671 | +Plasminogen activator inhibitor 1 | ||
672 | +p300 | ||
673 | +extent, type B receptors | ||
674 | +il12p40 | ||
675 | +miR-29c | ||
676 | +IL-1beta | ||
677 | +interleukin (IL)-17 | ||
678 | +transforming growth factor b(1) | ||
679 | +LTB(4) receptor | ||
680 | +BMP | ||
681 | +extracellular signal--regulated kinase | ||
682 | +interleukin-1 beta | ||
683 | +TLR4 | ||
684 | +AGT | ||
685 | +PP1 | ||
686 | +IGF-1 | ||
687 | +Thymosin b4 | ||
688 | +SOCS1 | ||
689 | +SMAD)2 | ||
690 | +E prostanoid receptor 2 | ||
691 | +b2 -AR | ||
692 | +microRNA (miR)-155 | ||
693 | +peroxisome proliferator-activated receptor-y | ||
694 | +Discoidin Domain Receptor 2 | ||
695 | +smad2/3 | ||
696 | +gp130 | ||
697 | +miR-31 | ||
698 | +MKL1 | ||
699 | +PPARalpha | ||
700 | +TTF-1 | ||
701 | +Erk1/2 | ||
702 | +ERK | ||
703 | +RXFP1 | ||
704 | +interleukin-18 | ||
705 | +protease nexin-1 | ||
706 | +Syndecan-2 | ||
707 | +RhoA | ||
708 | +CD34 | ||
709 | +N -cadherin | ||
710 | +Rta | ||
711 | +PI3K | ||
712 | +fibroblast specific protein-1 | ||
713 | +IGFBP-5 | ||
714 | +PDGB | ||
715 | +gremlin | ||
716 | +HMG-CoA) reductase | ||
717 | +Yin Yang 1 | ||
718 | +interleukin-1 | ||
719 | +p38 mitogen-activated protein kinase | ||
720 | +Vi | ||
721 | +CD11c | ||
722 | +IL-4 | ||
723 | +NEU1 | ||
724 | +VEGF | ||
725 | +CD46 | ||
726 | +protease-activated receptor (PAR)-2 | ||
727 | +C/EBP homologous protein | ||
728 | +ATG4B | ||
729 | +IKKa | ||
730 | +AKT2 | ||
731 | +calnexin | ||
732 | +CXCR3 | ||
733 | +peroxisome proliferator-activated receptor y | ||
734 | +fibroblast growth factor-2 | ||
735 | +TGF-beta receptor II | ||
736 | +CsA | ||
737 | +miR -221 | ||
738 | +BAX inhibitor-1 | ||
739 | +miR-5100 | ||
740 | +Ang-1 | ||
741 | +PEX13p | ||
742 | +SDC2 | ||
743 | +PARK2 | ||
744 | +5-HTR(1A/B) and 5-HTR(2B | ||
745 | +fibronectin | ||
746 | +interleukin (IL)-8 | ||
747 | +BMP-7 | ||
748 | +EP1 | ||
749 | +CDCP1 | ||
750 | +protease-activated receptor-2 | ||
751 | +CD8 | ||
752 | +CD206 | ||
753 | +TGF-beta receptors (T beta R-I and T beta R-II | ||
754 | +HGF | ||
755 | +c-Jun NH-terminal kinase | ||
756 | +Col3a1 | ||
757 | +IRAP | ||
758 | +Bcl-2 | ||
759 | +GLP-1 | ||
760 | +N-cadherin | ||
761 | +Sema 7a | ||
762 | +SDF-1 | ||
763 | +Wnt | ||
764 | +GLP-1 receptor | ||
765 | +sphingosine kinase 1 | ||
766 | +Smad2 | ||
767 | +transforming growth factor b-1 | ||
768 | +p63 | ||
769 | +TLR9 | ||
770 | +IL-13 | ||
771 | +X-linked inhibitor of apoptosis | ||
772 | +CD19 | ||
773 | +syndecan-2 | ||
774 | +EGR1 | ||
775 | +STUB1 | ||
776 | +Lysocardiolipin acyltransferase | ||
777 | +IL8, -6, and -1B | ||
778 | +Wnt1-inducible signaling protein 1 | ||
779 | +TGF-b | ||
780 | +tenascin | ||
781 | +hypoxia-inducible factor-1a | ||
782 | +IP-10 | ||
783 | +XIAP | ||
784 | +transforming growth factor beta1 | ||
785 | +caveolin-1 | ||
786 | +endothelial nitric oxide synthase | ||
787 | +IGF-2 | ||
788 | +CCR2 | ||
789 | +inducible nitric oxide synthase | ||
790 | +bone morphogenetic protein 7 | ||
791 | +platelet-derived growth factor, insulin-like growth factor type I, and transforming growth factor beta | ||
792 | +Itgb1/6 | ||
793 | +HIF-1 | ||
794 | +SRF | ||
795 | +miR-29a | ||
796 | +MPP-9 | ||
797 | +miR-155 | ||
798 | +PDGF-A and -B | ||
799 | +FoxO3a | ||
800 | +Cub domain containing protein 1 | ||
801 | +Muc5ac | ||
802 | +Yin yang 1 | ||
803 | +Transforming growth factor b | ||
804 | +Ltbp1 | ||
805 | +NOX-2 | ||
806 | +tissue inhibitor of metalloproteinase (TIMP)-1, -2, -3, and -4 | ||
807 | +Nox1 | ||
808 | +X-box-binding protein 1 | ||
809 | +miR-21 | ||
810 | +Wnt7B | ||
811 | +HSP90b | ||
812 | +PPAR-a | ||
813 | +leucine-rich alpha-2 glycoprotein | ||
814 | +TNF alpha | ||
815 | +estrogen receptor 1 | ||
816 | +TSLP | ||
817 | +signal transducer and activator of transcription 3 | ||
818 | +IL-8 and b-FGF | ||
819 | +matrix metalloproteinase-7 | ||
820 | +mitogen-activated protein kinase-activated protein kinase-2 | ||
821 | +Smad-3 | ||
822 | +matrix metalloproteinase (MMP)-9 | ||
823 | +beta 1 integrin | ||
824 | +interleukin (IL)-6 | ||
825 | +basic-fibroblast growth factor | ||
826 | +gastrin | ||
827 | +Pdgfb | ||
828 | +Itga2/3 | ||
829 | +HLF | ||
830 | +snail | ||
831 | +TGFb(1) | ||
832 | +Smurf2 | ||
833 | +STAT1 | ||
834 | +tissue factor | ||
835 | +Glucagon like peptide-1 | ||
836 | +NAC | ||
837 | +Lrp5 | ||
838 | +transforming growth factor b expression | ||
839 | +insulin-like growth factor (IGF)-I | ||
840 | +superoxide dismutase 3 | ||
841 | +vascular endothelial growth factor receptor | ||
842 | +Wt1 | ||
843 | +as c | ||
844 | +Transforming growth factor (TGF)-beta1 | ||
845 | +IGF-I | ||
846 | +UCP2 | ||
847 | +Protease activated receptor-1 | ||
848 | +G1 and G2 | ||
849 | +transforming growth factor beta-1 | ||
850 | +FHIT | ||
851 | +Wnt5A | ||
852 | +TGF beta1 | ||
853 | +MRTF-A | ||
854 | +platelet-derived growth factor receptor | ||
855 | +SphK1 | ||
856 | +extracellular superoxide dismutase | ||
857 | +Acta2 | ||
858 | +Toll-like receptor 4 | ||
859 | +ICAT | ||
860 | +CXCL10 | ||
861 | +alpha-SMA | ||
862 | +Bax inhibitor-1 | ||
863 | +keratin 6 and 14 | ||
864 | +AT2 | ||
865 | +MT1- and MT2-MMPs | ||
866 | +NOX1 | ||
867 | +beta 2 | ||
868 | +PAI-1-siRNA | ||
869 | +fibrillin-2 | ||
870 | +col3a1 | ||
871 | +IPF-1, insulin, and glucokinase | ||
872 | +cyclin D1 | ||
873 | +COX-2 | ||
874 | +CD4 | ||
875 | +MT2 | ||
876 | +Transforming growth factor-beta | ||
877 | +matrix metalloprotease-1 | ||
878 | +Thy-1 | ||
879 | +ATG7 | ||
880 | +neuraminidase 1 | ||
881 | +Mkl1 | ||
882 | +LPA1 | ||
883 | +Ost-4 | ||
884 | +MMP -9 | ||
885 | +HIF1a | ||
886 | +Semaphorin 7a | ||
887 | +EP3 | ||
888 | +Transforming growth factor-b1 | ||
889 | +PSAT1 | ||
890 | +High mobility group AT-hook 2 | ||
891 | +jagged 1 | ||
892 | +n-cadherin | ||
893 | +Janus kinase 2 | ||
894 | +let-7d | ||
895 | +Fas ligand | ||
896 | +integrin alpha v | ||
897 | +MK2(-/-) MEF | ||
898 | +interleukin-1beta | ||
899 | +p21 | ||
900 | +Col1a2 | ||
901 | +MT3-MMP | ||
902 | +PDGF-A | ||
903 | +JNK | ||
904 | +Transforming Growth Factor- b | ||
905 | +PP2A | ||
906 | +miR | ||
907 | +claudins-1, -3, and -5 | ||
908 | +BARD1 | ||
909 | +relaxin/insulin-like family peptide receptor 1 | ||
910 | +MMP2 | ||
911 | +ATG5 | ||
912 | +MEK | ||
913 | +CAV1 | ||
914 | +SIRT3 | ||
915 | +ANGII | ||
916 | +activin | ||
917 | +p38 MAPK | ||
918 | +interleukin-1 (IL-1)Ra | ||
919 | +hsa-miR-326 | ||
920 | +MAP3K19 | ||
921 | +surfactant protein C | ||
922 | +Nox4 | ||
923 | +collagen (Col)1a1 | ||
924 | +SAP | ||
925 | +miR-9-5p | ||
926 | +interleukin (IL)-1b | ||
927 | +p21(waf1 | ||
928 | +MicroRNA-29c | ||
929 | +H19 | ||
930 | +Protease-activated receptor-1 | ||
931 | +ALXR | ||
932 | +miR-487b | ||
933 | +TGF beta | ||
934 | +Connective tissue growth factor | ||
935 | +matrix metalloproteinase-14 | ||
936 | +SERPINE1 | ||
937 | +mir-21 | ||
938 | +CC chemokine receptor 2 | ||
939 | +PTEN | ||
940 | +IL-1 alpha | ||
941 | +IPF-1 | ||
942 | +c-IAP)1 | ||
943 | +Il-17a | ||
944 | +Pigment epithelium-derived factor | ||
945 | +fibroblast growth factor 10 | ||
946 | +connective-tissue growth factor | ||
947 | +BMP3 | ||
948 | +transforming growth factor-beta1 | ||
949 | +Annexin V | ||
950 | +HS6ST1/2 | ||
951 | +fibroblast growth factor-10 | ||
952 | +BI-1 | ||
953 | +lymphotactin | ||
954 | +tenascin-C | ||
955 | +miR-455 | ||
956 | +MT1-MMP | ||
957 | +transforming growth factor-b | ||
958 | +3-hydroxy-3-methylglutaryl CoenzymeA (HMG CoA) reductase | ||
959 | +SMAD2/3 | ||
960 | +MiR-338 | ||
961 | +MMP-2 and -9 | ||
962 | +LTBP)-1 | ||
963 | +suppressor of cytokine signaling 1 | ||
964 | +neutrophil peptide (HNP)-1 | ||
965 | +SphK2 | ||
966 | +S1P lyase | ||
967 | +ltbp1/2 | ||
968 | +iNOS | ||
969 | +TGFb(1 | ||
970 | +ACE | ||
971 | +BCL-2 | ||
972 | +Oct-4 | ||
973 | +SMA | ||
974 | +MMP-9 and tissue inhibitor of metalloproteinase-1 | ||
975 | +Hepatocyte growth factor | ||
976 | +Ets1 | ||
977 | +beta-actin | ||
978 | +VASH-1 | ||
979 | +CD117 | ||
980 | +THBS1 | ||
981 | +HO1 | ||
982 | +Hsp90 | ||
983 | +Extracellular Matrix Metalloproteinase Inducer | ||
984 | +COL1A1 | ||
985 | +AKT1 | ||
986 | +FGF-1 | ||
987 | +interleukin 6 | ||
988 | +caspase-3/7 | ||
989 | +IL6 | ||
990 | +receptor for advanced glycation end products | ||
991 | +EP4 | ||
992 | +TGFb | ||
993 | +HSP47 | ||
994 | +miR-140 | ||
995 | +heat shock protein (HSP)90 | ||
996 | +insulin-like growth factor binding proteins (IGFBP)-3 and -5 | ||
997 | +EZH2 | ||
998 | +Toll-Like Receptor 9 | ||
999 | +Col3A1 | ||
1000 | +Transforming Growth Factor- Beta1 | ||
1001 | +Osteopontin | ||
1002 | +hFL1 | ||
1003 | +CXCR4 | ||
1004 | +MMP19 | ||
1005 | +IL-33 | ||
1006 | +miR-17 92 | ||
1007 | +fibrillin-1 | ||
1008 | +ET-A | ||
1009 | +HDAC10 | ||
1010 | +ALK-5 | ||
1011 | +IL-31 | ||
1012 | +beclin 1 | ||
1013 | +c-Jun | ||
1014 | +Sema7a | ||
1015 | +MT5-MMP | ||
1016 | +PI3 | ||
1017 | +ITGB6 | ||
1018 | +TIAM1 | ||
1019 | +angiotensin II | ||
1020 | +LRG | ||
1021 | +IL-1alpha | ||
1022 | +TbetaRII | ||
1023 | +transforming growth factor b | ||
1024 | +FIEL1 | ||
1025 | +C5aR | ||
1026 | +PEDF | ||
1027 | +C1q | ||
1028 | +IL-1ra | ||
1029 | +tissue inhibitor of metalloproteinase | ||
1030 | +ErbB2 | ||
1031 | +TGF -b1 | ||
1032 | +PTEN-induced putative kinase 1 | ||
1033 | +AAG | ||
1034 | +CD103 | ||
1035 | +a-smooth muscle actin | ||
1036 | +cytokeratin 19 | ||
1037 | +CREB)-binding protein | ||
1038 | +p110a | ||
1039 | +Ets Domain-containing Protein Elk1 | ||
1040 | +insulin-like growth factor I | ||
1041 | +Cytokeratin-8 | ||
1042 | +TIMP3 | ||
1043 | +BMP-15 | ||
1044 | +LC3 | ||
1045 | +Vimentin | ||
1046 | +mTORC1 | ||
1047 | +SIRT6 | ||
1048 | +heme oxygenase-1 | ||
1049 | +Transforming growth factor-beta 1 | ||
1050 | +miR-127 | ||
1051 | +MIP-1 beta | ||
1052 | +TRPV4 | ||
1053 | +Neutrophil elastase | ||
1054 | +ANG converting enzyme | ||
1055 | +ERK-1 | ||
1056 | +bFGF | ||
1057 | +tumor necrosis factor-alpha | ||
1058 | +Serpin B3/B4 | ||
1059 | +focal adhesion kinase-related nonkinase | ||
1060 | +Stat3 | ||
1061 | +miR-1343 | ||
1062 | +SMAD7 | ||
1063 | +Endosialin | ||
1064 | +FGF-2 | ||
1065 | +miR-101 | ||
1066 | +L1CAM | ||
1067 | +thymic stromal lymphopoietin | ||
1068 | +vascular endothelial growth factor | ||
1069 | +PEX13 | ||
1070 | +heat shock protein (HSP) 47 | ||
1071 | +transient receptor potential vanilloid 4 | ||
1072 | +monocyte chemoattractant protein 1 | ||
1073 | +SPP1 | ||
1074 | +CD68 | ||
1075 | +TGF- b1 | ||
1076 | +T beta RII | ||
1077 | +TGFb-1 | ||
1078 | +Forkhead Box F1 |
tagging_Sklearn_crfsuite.py
deleted
100644 → 0
1 | -# -*- coding: UTF-8 -*- | ||
2 | - | ||
3 | -import os | ||
4 | -from itertools import chain | ||
5 | -from optparse import OptionParser | ||
6 | -from time import time | ||
7 | -from collections import Counter | ||
8 | - | ||
9 | -import nltk | ||
10 | -import sklearn | ||
11 | -import scipy.stats | ||
12 | -import sys | ||
13 | - | ||
14 | -from sklearn.externals import joblib | ||
15 | -from sklearn.metrics import make_scorer | ||
16 | -from sklearn.cross_validation import cross_val_score | ||
17 | -from sklearn.grid_search import RandomizedSearchCV | ||
18 | - | ||
19 | -import sklearn_crfsuite | ||
20 | -from sklearn_crfsuite import scorers | ||
21 | -from sklearn_crfsuite import metrics | ||
22 | - | ||
23 | -from nltk.corpus import stopwords | ||
24 | -from trainingTesting_Sklearn_crfsuite import word2features | ||
25 | -from trainingTesting_Sklearn_crfsuite import sent2features | ||
26 | -# from trainingTesting_Sklearn_crfsuite import hasNonAlphaNum | ||
27 | -# from trainingTesting_Sklearn_crfsuite import hasDigit | ||
28 | - | ||
29 | -# Objective | ||
30 | -# Tagging transformed file with CRF model with sklearn-crfsuite. | ||
31 | -# | ||
32 | -# Input parameters | ||
33 | -# --inputPath=PATH Path of transformed files x|y|z | ||
34 | -# --modelPath Path to CRF model | ||
35 | -# --modelName Model name | ||
36 | -# --outputPath=PATH Output path to place output files | ||
37 | -# --filteringStopWords Filtering stop words | ||
38 | -# --filterSymbols Filtering punctuation marks | ||
39 | - | ||
40 | -# Output | ||
41 | -# 1) Tagged files in transformed format | ||
42 | - | ||
43 | -# Examples | ||
44 | -# Sentences | ||
45 | -# C:\Anaconda2\python tagging_Sklearn_crfsuite.py --inputPath C:\Users\cmendezc\Documents\GENOMICAS\AUTOMATIC_SUMMARIZATION_TFS\classifying_TFSentences\corpus\ECK120011394_FhlA\transformed --modelName aspectsTraining.fStopWords_False.fSymbols_True --modelPath C:\Users\cmendezc\Documents\GENOMICAS\AUTOMATIC_SUMMARIZATION_TFS\trainingTest_CRF_TERM_TAGS --outputPath C:\Users\cmendezc\Documents\GENOMICAS\AUTOMATIC_SUMMARIZATION_TFS\classifying_TFSentences\corpus\ECK120011394_FhlA\transformed_CRFtagged --filterSymbols > output.taggingCRF.20161107.txt | ||
46 | -# C:\Anaconda2\python tagging_Sklearn_crfsuite.py --inputPath C:\Users\cmendezc\Documents\GENOMICAS\AUTOMATIC_SUMMARIZATION_TFS\classifying_TFSentences\corpus\ECK120011394_FhlA\transformed --modelName sentencesTraining.fStopWords_False.fSymbols_False --modelPath C:\Users\cmendezc\Documents\GENOMICAS\AUTOMATIC_SUMMARIZATION_TFS\trainingTest_CRF_TERM_TAGS --outputPath C:\Users\cmendezc\Documents\GENOMICAS\AUTOMATIC_SUMMARIZATION_TFS\classifying_TFSentences\corpus\ECK120011394_FhlA\transformed_CRFtagged > output.taggingCRF.20161107.txt | ||
47 | - | ||
48 | -################################# | ||
49 | -# FUNCTIONS # | ||
50 | -################################# | ||
51 | -# def hasDigit(text): | ||
52 | -# has = False | ||
53 | -# if len(text) < 3: | ||
54 | -# return False | ||
55 | -# myRegex = nltk.re.compile('[0-9]') | ||
56 | -# if myRegex.search(text) != None: | ||
57 | -# has = True | ||
58 | -# return has | ||
59 | -# | ||
60 | -# | ||
61 | -# def hasNonAlphaNum(text): | ||
62 | -# has = False | ||
63 | -# if len(text) < 3: | ||
64 | -# return False | ||
65 | -# myRegex = nltk.re.compile('\W') | ||
66 | -# if myRegex.search(text) != None: | ||
67 | -# has = True | ||
68 | -# return has | ||
69 | - | ||
70 | -# IMPORTED FROM TRAINING SCRIPT | ||
71 | -# def word2features(sent, i): | ||
72 | -# # print "i: " + str(i) | ||
73 | -# # print "sent[i]" + sent[i] | ||
74 | -# listElem = sent[i].split('|') | ||
75 | -# word = listElem[0] | ||
76 | -# lemma = listElem[1] | ||
77 | -# postag = listElem[2] | ||
78 | -# | ||
79 | -# features = { | ||
80 | -# # Names of TF and genes change by lower and upper characters: 'word.lower()': word.lower(), | ||
81 | -# # Suffixes | ||
82 | -# 'word[-3:]': word[-3:], | ||
83 | -# 'word[-2:]': word[-2:], | ||
84 | -# 'word[-1:]': word[-1:], | ||
85 | -# 'word.isupper()': word.isupper(), | ||
86 | -# 'word.istitle()': word.istitle(), | ||
87 | -# 'word.hasDigit()': hasDigit(word), | ||
88 | -# 'word.hasNonAlphaNum': hasNonAlphaNum(word), | ||
89 | -# # 'word.isdigit()': word.isdigit(), | ||
90 | -# 'word': word, | ||
91 | -# 'lemma': lemma, | ||
92 | -# 'lemma[-3:]': lemma[-3:], | ||
93 | -# 'lemma[-2:]': lemma[-2:], | ||
94 | -# 'lemma[-1:]': lemma[-1:], | ||
95 | -# 'postag': postag, | ||
96 | -# # Prefixes | ||
97 | -# 'postag[:2]': postag[:2], | ||
98 | -# 'postag[:1]': postag[:1], | ||
99 | -# } | ||
100 | -# if i > 0: | ||
101 | -# listElem = sent[i - 1].split('|') | ||
102 | -# word1 = listElem[0] | ||
103 | -# lemma1 = listElem[1] | ||
104 | -# postag1 = listElem[2] | ||
105 | -# features.update({ | ||
106 | -# '-1:word.lower()': word1.lower(), | ||
107 | -# '-1:word.istitle()': word1.istitle(), | ||
108 | -# '-1:word.isupper()': word1.isupper(), | ||
109 | -# '-1:word.hasDigit()': hasDigit(word1), | ||
110 | -# '-1:word.hasNonAlphaNum': hasNonAlphaNum(word1), | ||
111 | -# '-1:word': word1, | ||
112 | -# '-1:lemma': lemma1, | ||
113 | -# '-1:postag': postag1, | ||
114 | -# '-1:postag[:2]': postag1[:2], | ||
115 | -# '-1:postag[:1]': postag1[:1], | ||
116 | -# }) | ||
117 | -# # else: | ||
118 | -# # features['BOS'] = True | ||
119 | -# | ||
120 | -# if i < len(sent) - 1: | ||
121 | -# listElem = sent[i + 1].split('|') | ||
122 | -# word1 = listElem[0] | ||
123 | -# lemma1 = listElem[1] | ||
124 | -# postag1 = listElem[2] | ||
125 | -# features.update({ | ||
126 | -# '+1:word.lower()': word1.lower(), | ||
127 | -# '+1:word.istitle()': word1.istitle(), | ||
128 | -# '+1:word.isupper()': word1.isupper(), | ||
129 | -# '+1:word.hasDigit()': hasDigit(word1), | ||
130 | -# '+1:word.hasNonAlphaNum': hasNonAlphaNum(word1), | ||
131 | -# '+1:word': word1, | ||
132 | -# '+1:lemma': lemma1, | ||
133 | -# '+1:postag': postag1, | ||
134 | -# '+1:postag[:2]': postag1[:2], | ||
135 | -# '+1:postag[:1]': postag1[:1], | ||
136 | -# }) | ||
137 | -# # else: | ||
138 | -# # features['EOS'] = True | ||
139 | -# if i > 1: | ||
140 | -# listElem = sent[i - 2].split('|') | ||
141 | -# word2 = listElem[0] | ||
142 | -# lemma2 = listElem[1] | ||
143 | -# postag2 = listElem[2] | ||
144 | -# features.update({ | ||
145 | -# '-2:word.lower()': word2.lower(), | ||
146 | -# '-2:word.istitle()': word2.istitle(), | ||
147 | -# '-2:word.isupper()': word2.isupper(), | ||
148 | -# '-2:word.hasDigit()': hasDigit(word2), | ||
149 | -# '-2:word.hasNonAlphaNum': hasNonAlphaNum(word2), | ||
150 | -# '-2:word': word2, | ||
151 | -# '-2:lemma': lemma2, | ||
152 | -# '-2:postag': postag2, | ||
153 | -# '-2:postag[:2]': postag2[:2], | ||
154 | -# '-2:postag[:1]': postag2[:1], | ||
155 | -# }) | ||
156 | -# | ||
157 | -# if i < len(sent) - 2: | ||
158 | -# listElem = sent[i + 2].split('|') | ||
159 | -# word2 = listElem[0] | ||
160 | -# lemma2 = listElem[1] | ||
161 | -# postag2 = listElem[2] | ||
162 | -# features.update({ | ||
163 | -# '+2:word.lower()': word2.lower(), | ||
164 | -# '+2:word.istitle()': word2.istitle(), | ||
165 | -# '+2:word.isupper()': word2.isupper(), | ||
166 | -# '+2:word.hasDigit()': hasDigit(word2), | ||
167 | -# '+2:word.hasNonAlphaNum': hasNonAlphaNum(word2), | ||
168 | -# '+2:word': word2, | ||
169 | -# '+2:lemma': lemma2, | ||
170 | -# '+2:postag': postag2, | ||
171 | -# '+2:postag[:2]': postag2[:2], | ||
172 | -# '+2:postag[:1]': postag2[:1], | ||
173 | -# }) | ||
174 | -# | ||
175 | -# trigrams = False | ||
176 | -# if trigrams: | ||
177 | -# if i > 2: | ||
178 | -# listElem = sent[i - 3].split('|') | ||
179 | -# word3 = listElem[0] | ||
180 | -# lemma3 = listElem[1] | ||
181 | -# postag3 = listElem[2] | ||
182 | -# features.update({ | ||
183 | -# '-3:word.lower()': word3.lower(), | ||
184 | -# '-3:word.istitle()': word3.istitle(), | ||
185 | -# '-3:word.isupper()': word3.isupper(), | ||
186 | -# '-3:word.hasDigit()': hasDigit(word3), | ||
187 | -# '-3:word.hasNonAlphaNum': hasNonAlphaNum(word3), | ||
188 | -# '-3:word': word3, | ||
189 | -# '-3:lemma': lemma3, | ||
190 | -# '-3:postag': postag3, | ||
191 | -# '-3:postag[:2]': postag3[:2], | ||
192 | -# '-3:postag[:1]': postag3[:1], | ||
193 | -# }) | ||
194 | -# | ||
195 | -# if i < len(sent) - 3: | ||
196 | -# listElem = sent[i + 3].split('|') | ||
197 | -# word3 = listElem[0] | ||
198 | -# lemma3 = listElem[1] | ||
199 | -# postag3 = listElem[2] | ||
200 | -# features.update({ | ||
201 | -# '+3:word.lower()': word3.lower(), | ||
202 | -# '+3:word.istitle()': word3.istitle(), | ||
203 | -# '+3:word.isupper()': word3.isupper(), | ||
204 | -# '+3:word.hasDigit()': hasDigit(word3), | ||
205 | -# '+3:word.hasNonAlphaNum': hasNonAlphaNum(word3), | ||
206 | -# '+3:word': word3, | ||
207 | -# '+3:lemma': lemma3, | ||
208 | -# '+3:postag': postag3, | ||
209 | -# '+3:postag[:2]': postag3[:2], | ||
210 | -# '+3:postag[:1]': postag3[:1], | ||
211 | -# }) | ||
212 | -# | ||
213 | -# return features | ||
214 | - | ||
215 | - | ||
216 | -# def sent2features(sent): | ||
217 | -# return [word2features(sent, i) for i in range(len(sent))] | ||
218 | - | ||
219 | - | ||
220 | -__author__ = 'CMendezC' | ||
221 | - | ||
222 | -########################################## | ||
223 | -# MAIN PROGRAM # | ||
224 | -########################################## | ||
225 | - | ||
226 | -if __name__ == "__main__": | ||
227 | - # Defining parameters | ||
228 | - parser = OptionParser() | ||
229 | - parser.add_option("--inputPath", dest="inputPath", | ||
230 | - help="Path of training data set", metavar="PATH") | ||
231 | - parser.add_option("--outputPath", dest="outputPath", | ||
232 | - help="Output path to place output files", | ||
233 | - metavar="PATH") | ||
234 | - parser.add_option("--modelPath", dest="modelPath", | ||
235 | - help="Path to read CRF model", | ||
236 | - metavar="PATH") | ||
237 | - parser.add_option("--modelName", dest="modelName", | ||
238 | - help="Model name", metavar="TEXT") | ||
239 | - parser.add_option("--filterStopWords", default=False, | ||
240 | - action="store_true", dest="filterStopWords", | ||
241 | - help="Filtering stop words") | ||
242 | - parser.add_option("--filterSymbols", default=False, | ||
243 | - action="store_true", dest="filterSymbols", | ||
244 | - help="Filtering punctuation marks") | ||
245 | - | ||
246 | - (options, args) = parser.parse_args() | ||
247 | - if len(args) > 0: | ||
248 | - parser.error("Any parameter given.") | ||
249 | - sys.exit(1) | ||
250 | - | ||
251 | - print('-------------------------------- PARAMETERS --------------------------------') | ||
252 | - print("Path to read input files: " + options.inputPath) | ||
253 | - print("Mode name: " + str(options.modelName)) | ||
254 | - print("Model path: " + options.modelPath) | ||
255 | - print("Path to place output files: " + options.outputPath) | ||
256 | - print("Filtering stop words: " + str(options.filterStopWords)) | ||
257 | - symbols = ['.', ',', ':', ';', '?', '!', '\'', '"', '<', '>', '(', ')', '-', '_', '/', '\\', '¿', '¡', '+', '{', | ||
258 | - '}', '[', ']', '*', '%', '$', '#', '&', '°', '`', '...'] | ||
259 | - # symbols = [sym.decode('utf-8') for sym in ['.', ',', ':', ';', '?', '!', '\'', '"', '<', '>', '(', ')', '-', '_', '/', '\\', '¿', '¡', '+', '{', | ||
260 | - # '}', '[', ']', '*', '%', '$', '#', '&', '°']] | ||
261 | - # symbols = [u'.', u',', u':', u';', u'?', u'!', u'\'', u'"', u'<', u'>', u'(', u')', u'-', u'_', u'/', u'\\', u'¿', u'¡', u'+', u'{', | ||
262 | - # u'}', u'[', u']', u'*', u'%', u'$', u'#', u'&', u'°', u'`'] | ||
263 | - print("Filtering symbols " + str(symbols) + ': ' + str(options.filterSymbols)) | ||
264 | - | ||
265 | - print('-------------------------------- PROCESSING --------------------------------') | ||
266 | - | ||
267 | - stopwords = [word.decode('utf-8') for word in stopwords.words('english')] | ||
268 | - | ||
269 | - # Read CRF model | ||
270 | - t0 = time() | ||
271 | - print('Reading CRF model...') | ||
272 | - crf = joblib.load(os.path.join(options.modelPath, 'models', options.modelName + '.mod')) | ||
273 | - print("Reading CRF model done in: %fs" % (time() - t0)) | ||
274 | - | ||
275 | - print('Processing corpus...') | ||
276 | - t0 = time() | ||
277 | - labels = list(['MF', 'TF', 'DFAM', 'DMOT', 'DPOS', 'PRO']) | ||
278 | - # Walk directory to read files | ||
279 | - for path, dirs, files in os.walk(options.inputPath): | ||
280 | - # For each file in dir | ||
281 | - for file in files: | ||
282 | - print(" Preprocessing file..." + str(file)) | ||
283 | - sentencesInputData = [] | ||
284 | - sentencesOutputData = [] | ||
285 | - with open(os.path.join(options.inputPath, file), "r") as iFile: | ||
286 | - lines = iFile.readlines() | ||
287 | - for line in lines: | ||
288 | - listLine = [] | ||
289 | - # line = line.decode("utf-8") | ||
290 | - for token in line.strip('\n').split(): | ||
291 | - if options.filterStopWords: | ||
292 | - listToken = token.split('|') | ||
293 | - lemma = listToken[1] | ||
294 | - # Original if lemma in stopwords.words('english'): | ||
295 | - if lemma in stopwords: | ||
296 | - continue | ||
297 | - if options.filterSymbols: | ||
298 | - listToken = token.split('|') | ||
299 | - lemma = listToken[1] | ||
300 | - if lemma in symbols: | ||
301 | - if lemma == ',': | ||
302 | - print "Coma , identificada" | ||
303 | - continue | ||
304 | - listLine.append(token) | ||
305 | - sentencesInputData.append(listLine) | ||
306 | - print " Sentences input data: " + str(len(sentencesInputData)) | ||
307 | - # print sentencesInputData[0] | ||
308 | - # print(sent2features(sentencesInputData[0])[0]) | ||
309 | - # print(sent2labels(sentencesInputData[0])) | ||
310 | - X_input = [sent2features(s) for s in sentencesInputData] | ||
311 | - print(sent2features(sentencesInputData[0])[0]) | ||
312 | - # y_test = [sent2labels(s) for s in sentencesInputData] | ||
313 | - # Predicting tags | ||
314 | - t1 = time() | ||
315 | - print " Predicting tags with model" | ||
316 | - y_pred = crf.predict(X_input) | ||
317 | - print y_pred[0] | ||
318 | - print(" Prediction done in: %fs" % (time() - t1)) | ||
319 | - # Tagging with CRF model | ||
320 | - print " Tagging file" | ||
321 | - for line, tagLine in zip(lines, y_pred): | ||
322 | - outputLine = '' | ||
323 | - idx_tagLine = 0 | ||
324 | - line = line.strip('\n') | ||
325 | - print "\nLine: " + str(line) | ||
326 | - print "CRF tagged line: " + str(tagLine) | ||
327 | - for token in line.split(): | ||
328 | - listToken = token.split('|') | ||
329 | - word = listToken[0] | ||
330 | - lemma = listToken[1] | ||
331 | - tag = listToken[2] | ||
332 | - if options.filterStopWords: | ||
333 | - if lemma in stopwords: | ||
334 | - outputLine += token + ' ' | ||
335 | - continue | ||
336 | - if options.filterSymbols: | ||
337 | - if lemma in symbols: | ||
338 | - if lemma == ',': | ||
339 | - print "Coma , identificada" | ||
340 | - outputLine += token + ' ' | ||
341 | - continue | ||
342 | - CRFtag = tagLine[idx_tagLine] | ||
343 | - if (tag not in labels) and (CRFtag != 'O'): | ||
344 | - print "*** CRF change token {} to {}".format(token, CRFtag) | ||
345 | - outputLine += word + '|' + lemma + '|' + CRFtag + ' ' | ||
346 | - else: | ||
347 | - outputLine += word + '|' + lemma + '|' + tag + ' ' | ||
348 | - idx_tagLine += 1 | ||
349 | - sentencesOutputData.append(outputLine.rstrip()) | ||
350 | - with open(os.path.join(options.outputPath, file), "w") as oFile: | ||
351 | - for line in sentencesOutputData: | ||
352 | - oFile.write(line + '\n') | ||
353 | - | ||
354 | - print("Processing corpus done in: %fs" % (time() - t0)) |
... | @@ -198,8 +198,8 @@ if __name__ == "__main__": | ... | @@ -198,8 +198,8 @@ if __name__ == "__main__": |
198 | 198 | ||
199 | print("Reading corpus done in: %fs" % (time() - t0)) | 199 | print("Reading corpus done in: %fs" % (time() - t0)) |
200 | 200 | ||
201 | - print(sent2features(sentencesTrainingData[0])[0]) | 201 | + #print(sent2features(sentencesTrainingData[0])[0]) |
202 | - print(sent2features(sentencesTestData[0])[0]) | 202 | + #print(sent2features(sentencesTestData[0])[0]) |
203 | t0 = time() | 203 | t0 = time() |
204 | 204 | ||
205 | X_train = [sent2features(s) for s in sentencesTrainingData] | 205 | X_train = [sent2features(s) for s in sentencesTrainingData] | ... | ... |
-
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