Made visual enhancements

app.py

@@ -44,7 +44,7 @@ def create_scoring_matrix_visual(scores,sequence,AA_vocab=AA_vocab,mutation_rang
   scores_dict = {}
   valid_mutant_set=set(scores.mutant)
   if mutation_range_start is None: mutation_range_start=1
-  if mutation_range_end is None: mutation_range_start=len(sequence)
+  if mutation_range_end is None: mutation_range_end=len(sequence)
   for target_AA in list(AA_vocab):
     for position in range(mutation_range_start,mutation_range_end+1):
       mutant = sequence[position-1]+str(position)+target_AA
@@ -109,16 +109,17 @@ def score_and_create_matrix_all_singles(sequence,mutation_range_start=None,mutat
 
 title = "Interactive in silico directed evolution with Tranception"
 description = "Perform in silico directed evolution with Tranception to iteratively improve the fitness of a starting protein sequence one mutation at a time. At each step, the Tranception model computes the log likelihood ratios of all possible single amino acid substitution Vs the starting sequence, and outputs a fitness heatmap and recommandations to guide the selection of the mutation to apply. Note: The current version does not currently leverage homologs retrieval at inference time to boost fitness prediction performance."
-article = "<p style='text-align: center'><a href='https://proceedings.mlr.press/v162/notin22a.html' target='_blank'>Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval</a></p>"
+article = "<p style='text-align: left'>**Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval**</p>"
+article += "<br><p style='text-align: left'> Pascal Notin, Mafalda Dias, Jonathan Frazer, Javier Marchena-Hurtado, Aidan N. Gomez, Debora S. Marks<sup>*</sup>, Yarin Gal<sup>*</sup>"
+article += "<br><p style='text-align: left'> <a href='https://proceedings.mlr.press/v162/notin22a.html' target='_blank'>Paper</a> *** <a href='https://github.com/OATML-Markslab/Tranception' target='_blank'>Code</a> </p>
 examples=[
-['A4_HUMAN: MLPGLALLLLAAWTARALEVPTDGNAGLLAEPQIAMFCGRLNMHMNVQNGKWDSDPSGTKTCIDTKEGILQYCQEVYPELQITNVVEANQPVTIQNWCKRGRKQCKTHPHFVIPYRCLVGEFVSDALLVPDKCKFLHQERMDVCETHLHWHTVAKETCSEKSTNLHDYGMLLPCGIDKFRGVEFVCCPLAEESDNVDSADAEEDDSDVWWGGADTDYADGSEDKVVEVAEEEEVAEVEEEEADDDEDDEDGDEVEEEAEEPYEEATERTTSIATTTTTTTESVEEVVREVCSEQAETGPCRAMISRWYFDVTEGKCAPFFYGGCGGNRNNFDTEEYCMAVCGSAMSQSLLKTTQEPLARDPVKLPTTAASTPDAVDKYLETPGDENEHAHFQKAKERLEAKHRERMSQVMREWEEAERQAKNLPKADKKAVIQHFQEKVESLEQEAANERQQLVETHMARVEAMLNDRRRLALENYITALQAVPPRPRHVFNMLKKYVRAEQKDRQHTLKHFEHVRMVDPKKAAQIRSQVMTHLRVIYERMNQSLSLLYNVPAVAEEIQDEVDELLQKEQNYSDDVLANMISEPRISYGNDALMPSLTETKTTVELLPVNGEFSLDDLQPWHSFGADSVPANTENEVEPVDARPAADRGLTTRPGSGLTNIKTEEISEVKMDAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVVIATVIVITLVMLKKKQYTSIHHGVVEVDAAVTPEERHLSKMQQNGYENPTYKFFEQMQN'],
-['ADRB2_HUMAN: MGQPGNGSAFLLAPNGSHAPDHDVTQERDEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYANETCCDFFTNQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLQKIDKSEGRFHVQNLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNPLIYCRSPDFRIAFQELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQGTVPSDNIDSQGRNCSTNDSLL'],
-['AMIE_PSEAE: MRHGDISSSNDTVGVAVVNYKMPRLHTAAEVLDNARKIAEMIVGMKQGLPGMDLVVFPEYSLQGIMYDPAEMMETAVAIPGEETEIFSRACRKANVWGVFSLTGERHEEHPRKAPYNTLVLIDNNGEIVQKYRKIIPWCPIEGWYPGGQTYVSEGPKGMKISLIICDDGNYPEIWRDCAMKGAELIVRCQGYMYPAKDQQVMMAKAMAWANNCYVAVANAAGFDGVYSYFGHSAIIGFDGRTLGECGEEEMGIQYAQLSLSQIRDARANDQSQNHLFKILHRGYSGLQASGDGDRGLAECPFEFYRTWVTDAEKARENVERLTRSTTGVAQCPVGRLPYEGLEKEA'],
-['P53_HUMAN: MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGPDEAPRMPEAAPRVAPAPAAPTPAAPAPAPSWPLSSSVPSQKTYQGSYGFRLGFLHSGTAKSVTCTYSPALNKMFCQLAKTCPVQLWVDSTPPPGTRVRAMAIYKQSQHMTEVVRRCPHHERCSDSDGLAPPQHLIRVEGNLRVEYLDDRNTFRHSVVVPYEPPEVGSDCTTIHYNYMCNSSCMGGMNRRPILTIITLEDSSGNLLGRNSFEVRVCACPGRDRRTEEENLRKKGEPHHELPPGSTKRALPNNTSSSPQPKKKPLDGEYFTLQIRGRERFEMFRELNEALELKDAQAGKEPGGSRAHSSHLKSKKGQSTSRHKKLMFKTEGPDSD']
+['ADRB2_HUMAN --> MGQPGNGSAFLLAPNGSHAPDHDVTQERDEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYANETCCDFFTNQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLQKIDKSEGRFHVQNLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNPLIYCRSPDFRIAFQELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQGTVPSDNIDSQGRNCSTNDSLL', 1, 10, "Small", True],
+['IF1_ECOLI --> MAKEDNIEMQGTVLETLPNTMFRVELENGHVVTAHISGKMRKNYIRILTGDKVTVELTPYDLSKGRIVFRSR', 1, None, "Medium", False],
+['P53_HUMAN --> MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGPDEAPRMPEAAPRVAPAPAAPTPAAPAPAPSWPLSSSVPSQKTYQGSYGFRLGFLHSGTAKSVTCTYSPALNKMFCQLAKTCPVQLWVDSTPPPGTRVRAMAIYKQSQHMTEVVRRCPHHERCSDSDGLAPPQHLIRVEGNLRVEYLDDRNTFRHSVVVPYEPPEVGSDCTTIHYNYMCNSSCMGGMNRRPILTIITLEDSSGNLLGRNSFEVRVCACPGRDRRTEEENLRKKGEPHHELPPGSTKRALPNNTSSSPQPKKKPLDGEYFTLQIRGRERFEMFRELNEALELKDAQAGKEPGGSRAHSSHLKSKKGQSTSRHKKLMFKTEGPDSD', 5, 10, "Large", False]
 ]
 
 model_size_selection = gr.Radio(label="Tranception model size (larger models are more accurate but are slower at inference)", choices=["Small","Medium","Large"], value="Small")
-protein_sequence_input = gr.Textbox(lines=1, label="Input protein sequence (see below for examples; default = RL40A_YEAST)",value="MQIFVKTLTGKTITLEVESSDTIDNVKSKIQDKEGIPPDQQRLIFAGKQLEDGRTLSDYNIQKESTLHLVLRLRGGIIEPSLKALASKYNCDKSVCRKCYARLPPRATNCRKRKCGHTNQLRPKKKLK")
+protein_sequence_input = gr.Textbox(lines=1, label="Input protein sequence (default = RL40A_YEAST)",value="MQIFVKTLTGKTITLEVESSDTIDNVKSKIQDKEGIPPDQQRLIFAGKQLEDGRTLSDYNIQKESTLHLVLRLRGGIIEPSLKALASKYNCDKSVCRKCYARLPPRATNCRKRKCGHTNQLRPKKKLK")
 mutation_range_start = gr.Number(label="Start of mutation range (min value = 1)",value=1,precision=0)
 mutation_range_end = gr.Number(label="End of mutation range (leave empty for full lenth)",value=10,precision=0)
 scoring_mirror = gr.Checkbox(label="Score protein from both directions (leads to more robust fitness predictions, but doubles inference time)")
@@ -130,10 +131,10 @@ output_recommendations = gr.Textbox(label="Mutation recommendations")
 gr.Interface(
     fn=score_and_create_matrix_all_singles,
     inputs=[protein_sequence_input,mutation_range_start,mutation_range_end,model_size_selection,scoring_mirror],
-    outputs=["plot","text"],
+    outputs=[output_plot,output_recommendations],
     title=title,
     description=description,
     article=article,
-    #examples=examples,
+    examples=examples,
     allow_flagging="never"
 ).launch(debug=True)