fixed typos

notebooks/running_jobs_complexes.ipynb

@@ -63,18 +63,18 @@
     "1) In \"align_1\" and \"align_2\" section:\n",
     "* __alignment_protocol__: choose either 'existing' to use an input alignment or 'standard' to generate an alignment\n",
     "using the monomer alignment protocol.\n",
-    "* __input_alignment__: input alignment file, requried for 'existing' alignment protocol\n",
+    "* __input_alignment__: input alignment file, required for 'existing' alignment protocol\n",
     "* __override_annotation_file__: input annotation file, required for 'existing' alignment protocol when using best_hit concatenation. This is the \\_annotations.csv file from the same monomer pipeline run used to generate the input alignment, OR a user-generated .csv file with columns \"id\" containing the full sequence ids from the alignment and column \"OS\" that contains annotation information for each id. This will override the incomplete annotations generated when postprocessing the input_alignment.\n",
     "\n",
     "3) in \"concatenate\" section:\n",
-    "* __protocol__: currently two procols are available. Genome_distance will pair sequences by closest reciprocal distance on the genome. Best_hit will pair by best hit to the target sequence for each genome. \n",
+    "* __protocol__: currently two protocols are available. Genome_distance will pair sequences by closest reciprocal distance on the genome. Best_hit will pair by best hit to the target sequence for each genome. \n",
     "* __use_best_reciprocal__: if using the best_hit protocol, use_best_reciprocal specifies whether to only take the best reciprocal hit in each genome\n",
     "* __minimum_sequence_coverage__: After concatenation, only keep concatenated sequences that align to at least x% of the target concatenated sequence \n",
     "* __minimum_column_coverage__: After concatenation, only include alignment columns with at least x% residues (rather than gaps) during model inference. \n",
     "\n",
     "4) in \"couplings\" section:\n",
     "* __scoring__: Options are skewnormal, lognormal, and evcomplex. Scoring model to assess confidence in computed ECs\n",
-    "* __use_all_ecs_for_scoring__: if True, will run the scoring model on the ECs, both inter and intra, simulataneously. If false, scoring will be done for monomer 1, monomer 2, and inter-protein ECs independently. \n",
+    "* __use_all_ecs_for_scoring__: if True, will run the scoring model on the ECs, both inter and intra, simultaneously. If false, scoring will be done for monomer 1, monomer 2, and inter-protein ECs independently. \n",
     "\n",
     "5) in \"compare\" section:\n",
     "\n",