diff --git a/.travis.yml b/.travis.yml
index b000eb2..2d0e18a 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -4,7 +4,7 @@ sudo: true
 language: python
 python:
   - "2.7"
-  - "3.6"
+  - "3.5"
 git:
   # don't need the default depth of 50
   # but don't want to use a depth of 1 since that affects
@@ -57,7 +57,7 @@ addons:
 install:
   - >
       conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION
-      numpy nose pylint cython
+      numpy nose pylint cython tensorflow tensorboard
   - source activate test-environment
   # install pysam from conda because I'm having trouble installing Cython
   # for Python 3 on Travis
diff --git a/setup.py b/setup.py
index dfd7fec..e3ddee7 100644
--- a/setup.py
+++ b/setup.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -45,12 +43,12 @@
         name='vaxrank',
         version=version,
         description="Mutant peptide ranking for personalized cancer vaccines",
-        author="Alex Rubinsteyn",
-        author_email="alex.rubinsteyn@gmail.com",
-        url="https://github.com/hammerlab/vaxrank",
+        author="Alex Rubinsteyn, Julia Kodysh",
+        author_email="alex@openvax.org, julia@openvax.org",
+        url="https://github.com/openvax/vaxrank",
         license="http://www.apache.org/licenses/LICENSE-2.0.html",
         classifiers=[
-            'Development Status :: 3 - Alpha',
+            'Development Status :: 4 - Beta',
             'Environment :: Console',
             'Operating System :: OS Independent',
             'Intended Audience :: Science/Research',
diff --git a/test/test_cancer_driver_gene.py b/test/test_cancer_driver_gene.py
index 3e4552e..b9a3fe9 100644
--- a/test/test_cancer_driver_gene.py
+++ b/test/test_cancer_driver_gene.py
@@ -1,3 +1,16 @@
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
 from vaxrank.gene_pathway_check import (
     GenePathwayCheck,
     _IFNG_RESPONSE_COLUMN_NAME,
diff --git a/test/test_epitope_prediction.py b/test/test_epitope_prediction.py
index 789a338..72c03a5 100644
--- a/test/test_epitope_prediction.py
+++ b/test/test_epitope_prediction.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -19,7 +17,7 @@
 from mhctools import RandomBindingPredictor
 from pyensembl import genome_for_reference_name
 from varcode import Variant
-from vaxrank.epitope_prediction import predict_epitopes
+from vaxrank.epitope_prediction import predict_epitopes, EpitopePrediction
 from vaxrank.mutant_protein_fragment import MutantProteinFragment
 from vaxrank.vaccine_peptide import VaccinePeptide
 
@@ -89,3 +87,20 @@ def predict_subsequences(self, x):
         genome=mouse_genome)
 
     eq_(0, len(epitope_predictions))
+
+def test_EpitopePrediction_json_serialization():
+    e = EpitopePrediction(
+        allele="HLA-A*02:01",
+        peptide_sequence="SIINFEQL",
+        ic50=2.0,
+        wt_peptide_sequence="SIINFEKL",
+        wt_ic50=2000.0,
+        percentile_rank=0.3,
+        prediction_method_name="ImaginationMHCpan",
+        overlaps_mutation=True,
+        source_sequence="SSIINFEQL",
+        offset=1,
+        occurs_in_reference=False)
+    json = e.to_json()
+    e2 = EpitopePrediction.from_json(json)
+    eq_(e, e2)
diff --git a/test/test_manufacturability.py b/test/test_manufacturability.py
index 740ef4d..fc39535 100644
--- a/test/test_manufacturability.py
+++ b/test/test_manufacturability.py
@@ -1,3 +1,16 @@
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
 from vaxrank.manufacturability import ManufacturabilityScores
 
 
diff --git a/test/test_mutant_protein_sequence.py b/test/test_mutant_protein_sequence.py
index 598acce..55cc822 100644
--- a/test/test_mutant_protein_sequence.py
+++ b/test/test_mutant_protein_sequence.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
diff --git a/test/test_shell_script.py b/test/test_shell_script.py
index acfde3f..02465e7 100644
--- a/test/test_shell_script.py
+++ b/test/test_shell_script.py
@@ -1,3 +1,16 @@
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
 from os.path import getsize
 from mock import patch
 from nose.plugins.attrib import attr
diff --git a/test/testing_helpers.py b/test/testing_helpers.py
index 22248a1..3b241ac 100644
--- a/test/testing_helpers.py
+++ b/test/testing_helpers.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
diff --git a/vaxrank/__init__.py b/vaxrank/__init__.py
index 7863915..6849410 100644
--- a/vaxrank/__init__.py
+++ b/vaxrank/__init__.py
@@ -1 +1 @@
-__version__ = "1.0.2"
+__version__ = "1.1.0"
diff --git a/vaxrank/cli.py b/vaxrank/cli.py
index d0426e9..51cc09d 100644
--- a/vaxrank/cli.py
+++ b/vaxrank/cli.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -42,8 +40,8 @@
     make_csv_report,
     make_minimal_neoepitope_report,
     TemplateDataCreator,
-    PatientInfo,
 )
+from .patient_info import PatientInfo
 
 logger = logging.getLogger(__name__)
 
diff --git a/vaxrank/core_logic.py b/vaxrank/core_logic.py
index 6db6a26..9cfc904 100644
--- a/vaxrank/core_logic.py
+++ b/vaxrank/core_logic.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
diff --git a/vaxrank/epitope_prediction.py b/vaxrank/epitope_prediction.py
index eebd6b2..c133e1e 100644
--- a/vaxrank/epitope_prediction.py
+++ b/vaxrank/epitope_prediction.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -13,33 +11,57 @@
 # limitations under the License.
 
 from __future__ import absolute_import, print_function, division
-from collections import namedtuple, OrderedDict
+from collections import OrderedDict
 import traceback
 import logging
 
 import numpy as np
+from serializable import Serializable
 
 from .reference_proteome import ReferenceProteome
 
-logger = logging.getLogger(__name__)
 
-EpitopePredictionBase = namedtuple("EpitopePrediction", [
-    "allele",
-    "peptide_sequence",
-    "wt_peptide_sequence",
-    "length",
-    "ic50",
-    "wt_ic50",
-    "percentile_rank",
-    "prediction_method_name",
-    "overlaps_mutation",
-    "source_sequence",
-    "offset",
-    "occurs_in_reference",
-])
+logger = logging.getLogger(__name__)
 
 
-class EpitopePrediction(EpitopePredictionBase):
+class EpitopePrediction(Serializable):
+    def __init__(
+            self,
+            allele,
+            peptide_sequence,
+            wt_peptide_sequence,
+            ic50,
+            wt_ic50,
+            percentile_rank,
+            prediction_method_name,
+            overlaps_mutation,
+            source_sequence,
+            offset,
+            occurs_in_reference):
+        self.allele = allele
+        self.peptide_sequence = peptide_sequence
+        self.wt_peptide_sequence = wt_peptide_sequence
+        self.length = len(peptide_sequence)
+        self.ic50 = ic50
+        self.wt_ic50 = wt_ic50
+        self.percentile_rank = percentile_rank
+        self.prediction_method_name = prediction_method_name
+        self.overlaps_mutation = overlaps_mutation
+        self.source_sequence = source_sequence
+        self.offset = offset
+        self.overlaps_mutation = overlaps_mutation
+        self.occurs_in_reference = occurs_in_reference
+
+    @classmethod
+    def from_dict(cls, d):
+        """
+        Deserialize EpitopePrediction from a dictionary of keywords.
+        """
+        d = d.copy()
+        if "length" in d:
+            # length argument removed in version 1.1.0
+            del d["length"]
+        return cls(**d)
 
     def logistic_epitope_score(
             self,
@@ -70,6 +92,56 @@ def logistic_epitope_score(
 
         return logistic / normalizer
 
+    def slice_source_sequence(self, start_offset, end_offset):
+        """
+
+        Parameters
+        ----------
+        start_offset : int
+
+        end_offset : int
+
+        Return EpitopePrediction object with source sequence and offset
+        adjusted. If this slicing would shorten the mutant peptide, then
+        return None.
+        """
+        if self.offset < start_offset:
+            # this peptide starts before the requested slice through the
+            # source sequence
+            return None
+
+        if self.offset + self.length > end_offset:
+            # this peptide goes beyond the end of the requested slice
+            # through the source sequence
+            return None
+
+        return EpitopePrediction(
+            allele=self.allele,
+            peptide_sequence=self.peptide_sequence,
+            wt_peptide_sequence=self.wt_peptide_sequence,
+            ic50=self.ic50,
+            wt_ic50=self.wt_ic50,
+            percentile_rank=self.percentile_rank,
+            prediction_method_name=self.prediction_method_name,
+            overlaps_mutation=self.overlaps_mutation,
+            source_sequence=self.source_sequence[start_offset:end_offset],
+            offset=self.offset - start_offset,
+            occurs_in_reference=self.occurs_in_reference)
+
+
+def slice_epitope_predictions(
+        epitope_predictions,
+        start_offset,
+        end_offset):
+    """
+    Return subset of EpitopePrediction objects which overlap the given interval
+    and slice through their source sequences and adjust their offset.
+    """
+    return [
+        p.slice_source_sequence(start_offset, end_offset)
+        for p in epitope_predictions
+        if p.offset >= start_offset and p.offset + p.length <= end_offset
+    ]
 
 def predict_epitopes(
         mhc_predictor,
@@ -150,10 +222,11 @@ def predict_epitopes(
             'MHC prediction for WT peptides errored, with traceback: %s',
             traceback.format_exc())
 
-    wt_predictions_grouped = {}
     # break it out: (peptide, allele) -> prediction
-    for wt_prediction in wt_predictions:
-        wt_predictions_grouped[(wt_prediction.peptide, wt_prediction.allele)] = wt_prediction
+    wt_predictions_grouped = {
+        (wt_prediction.peptide, wt_prediction.allele): wt_prediction
+        for wt_prediction in wt_predictions
+    }
 
     # convert from mhctools.BindingPrediction objects to EpitopePrediction
     # which differs primarily by also having a boolean field
@@ -181,7 +254,8 @@ def predict_epitopes(
         # compute WT epitope sequence, if this epitope overlaps the mutation
         if overlaps_mutation:
             wt_peptide = wt_peptides[peptide]
-            wt_prediction = wt_predictions_grouped.get((wt_peptide, binding_prediction.allele))
+            wt_prediction = wt_predictions_grouped.get(
+                (wt_peptide, binding_prediction.allele))
             wt_ic50 = None
             if wt_prediction is None:
                 # this can happen in a stop-loss variant: do we want to check that here?
@@ -200,7 +274,6 @@ def predict_epitopes(
             allele=binding_prediction.allele,
             peptide_sequence=peptide,
             wt_peptide_sequence=wt_peptide,
-            length=len(peptide),
             ic50=binding_prediction.value,
             wt_ic50=wt_ic50,
             percentile_rank=binding_prediction.percentile_rank,
@@ -209,6 +282,7 @@ def predict_epitopes(
             source_sequence=protein_fragment.amino_acids,
             offset=peptide_start_offset,
             occurs_in_reference=occurs_in_reference)
+
         if epitope_prediction.logistic_epitope_score() >= min_epitope_score:
             key = (epitope_prediction.peptide_sequence, epitope_prediction.allele)
             results[key] = epitope_prediction
@@ -221,30 +295,3 @@ def predict_epitopes(
         num_occurs_in_reference,
         num_low_scoring)
     return results
-
-
-def slice_epitope_predictions(
-        epitope_predictions,
-        start_offset,
-        end_offset):
-    """
-    Return subset of EpitopePrediction objects which overlap the given interval
-    and slice through their source sequences and adjust their offset.
-    """
-    return [
-        EpitopePrediction(
-            allele=p.allele,
-            peptide_sequence=p.peptide_sequence,
-            wt_peptide_sequence=p.wt_peptide_sequence,
-            length=p.length,
-            ic50=p.ic50,
-            wt_ic50=p.wt_ic50,
-            percentile_rank=p.percentile_rank,
-            prediction_method_name=p.prediction_method_name,
-            overlaps_mutation=p.overlaps_mutation,
-            source_sequence=p.source_sequence[start_offset:end_offset],
-            offset=p.offset - start_offset,
-            occurs_in_reference=p.occurs_in_reference)
-        for p in epitope_predictions
-        if p.offset >= start_offset and p.offset + p.length <= end_offset
-    ]
diff --git a/vaxrank/gene_pathway_check.py b/vaxrank/gene_pathway_check.py
index 698ef39..91131f7 100644
--- a/vaxrank/gene_pathway_check.py
+++ b/vaxrank/gene_pathway_check.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
diff --git a/vaxrank/manufacturability.py b/vaxrank/manufacturability.py
index 5034c03..36d9d70 100644
--- a/vaxrank/manufacturability.py
+++ b/vaxrank/manufacturability.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
diff --git a/vaxrank/mutant_protein_fragment.py b/vaxrank/mutant_protein_fragment.py
index e60c9b0..0b90c4b 100644
--- a/vaxrank/mutant_protein_fragment.py
+++ b/vaxrank/mutant_protein_fragment.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -14,57 +12,77 @@
 
 from __future__ import absolute_import, print_function, division
 
-from collections import namedtuple
 import logging
 
 from varcode.effects import top_priority_effect
-
+from serializable import Serializable
 
 logger = logging.getLogger(__name__)
 
-# using a namedtuple base class for the immutable fields of a MutantProteinFragment
-# since it makes it clearer what the essential information is and provides
-# useful comparison/hashing methods
-
-MutantProteinFragmentBase = namedtuple("MutantProteinFragment", (
-    # varcode.Variant
-    "variant",
-    # gene and transcript(s) which were used to translate one or more
-    # variant cDNA sequences into the following amino acids
-    "gene_name",
-
-    ###
-    # Translated protein sequence, aggregated from possibly multiple
-    # synonymous coding sequences
-    ###
-
-    "amino_acids",
-    # offsets of amino acids which differ due to the mutation
-    "mutant_amino_acid_start_offset",
-    "mutant_amino_acid_end_offset",
-
-    # PyEnsembl Transcript objects for reference transcripts which
-    # were used to establish the reading frame of coding sequence(s)
-    # detected from RNA
-    "supporting_reference_transcripts",
-
-    ###
-    # RNA evidence
-    ###
-
-    # number of reads overlapping the variant locus
-    "n_overlapping_reads",
-    # number of reads supporting the variant
-    "n_alt_reads",
-    # number of reads supporting the reference allele
-    "n_ref_reads",
-
-    # number of RNA reads fully spanning the cDNA sequence(s) from which we
-    # translated this amino acid sequence.
-    "n_alt_reads_supporting_protein_sequence",
-))
-
-class MutantProteinFragment(MutantProteinFragmentBase):
+
+class MutantProteinFragment(Serializable):
+    def __init__(
+            self,
+            variant,
+            gene_name,
+            amino_acids,
+            mutant_amino_acid_start_offset,
+            mutant_amino_acid_end_offset,
+            supporting_reference_transcripts,
+            n_overlapping_reads,
+            n_alt_reads,
+            n_ref_reads,
+            n_alt_reads_supporting_protein_sequence):
+        """
+        Parameters
+        ----------
+        variant : varcode.Variant
+            Somatic mutation.
+
+        gene_name : str
+            Gene from which we used a transcript to translate this mutation.
+
+        amino_acids : str
+            Translated protein sequence, aggregated from possibly multiple
+            synonymous coding sequences.
+
+        mutant_amino_acid_start_offset : int
+            Starting offset of amino acids which differ due to the mutation
+
+        mutant_amino_acid_end_offset : int
+            End offset of amino acids which differ due to the mutation
+
+        supporting_reference_transcripts : list of pyensembl.Transcript
+            PyEnsembl Transcript objects for reference transcripts which
+            were used to establish the reading frame of coding sequence(s)
+            detected from RNA.
+
+        n_overlapping_reads : int
+            Number of reads overlapping the variant locus.
+
+        n_alt_reads  : int
+            Number of reads supporting the variant.
+
+        n_ref_reads : int
+            Number of reads supporting the reference allele.
+
+        n_alt_reads_supporting_protein_sequence : int
+            Number of RNA reads fully spanning the cDNA sequence(s) from which
+            we translated this amino acid sequence.
+        """
+        self.variant = variant
+        self.gene_name = gene_name
+        self.amino_acids = amino_acids
+        self.mutant_amino_acid_start_offset = mutant_amino_acid_start_offset
+        self.mutant_amino_acid_end_offset = mutant_amino_acid_end_offset
+        self.supporting_reference_transcripts = \
+            supporting_reference_transcripts
+        self.n_overlapping_reads = n_overlapping_reads
+        self.n_alt_reads = n_alt_reads
+        self.n_ref_reads = n_ref_reads
+        self.n_alt_reads_supporting_protein_sequence = \
+            n_alt_reads_supporting_protein_sequence
+
     @classmethod
     def from_isovar_protein_sequence(cls, variant, protein_sequence):
         return cls(
@@ -185,7 +203,8 @@ def global_start_pos(self):
         # position of mutation start relative to the full amino acid sequence
         global_mutation_start_pos = self.predicted_effect().aa_mutation_start_offset
         if global_mutation_start_pos is None:
-            logger.error('Could not find mutation start pos for variant %s',
+            logger.error(
+                'Could not find mutation start pos for variant %s',
                 self.variant)
             return -1
 
diff --git a/vaxrank/patient_info.py b/vaxrank/patient_info.py
new file mode 100644
index 0000000..6418247
--- /dev/null
+++ b/vaxrank/patient_info.py
@@ -0,0 +1,21 @@
+from serializable import Serializable
+
+class PatientInfo(Serializable):
+    def __init__(
+            self,
+            patient_id,
+            vcf_paths,
+            bam_path,
+            mhc_alleles,
+            num_somatic_variants,
+            num_coding_effect_variants,
+            num_variants_with_rna_support,
+            num_variants_with_vaccine_peptides):
+        self.patient_id = patient_id
+        self.vcf_paths = vcf_paths
+        self.bam_path = bam_path
+        self.mhc_alleles = mhc_alleles
+        self.num_somatic_variants = num_somatic_variants
+        self.num_coding_effect_variants = num_coding_effect_variants
+        self.num_variants_with_rna_support = num_variants_with_rna_support
+        self.num_variants_with_vaccine_peptides = num_variants_with_vaccine_peptides
diff --git a/vaxrank/reference_proteome.py b/vaxrank/reference_proteome.py
index ed2f79f..4f15d45 100644
--- a/vaxrank/reference_proteome.py
+++ b/vaxrank/reference_proteome.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
diff --git a/vaxrank/report.py b/vaxrank/report.py
index 63bd1a2..9b4560f 100644
--- a/vaxrank/report.py
+++ b/vaxrank/report.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016-2018. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -12,8 +10,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+# pylint: disable=abstract-class-instantiated
+# For more details see https://github.com/PyCQA/pylint/issues/3060
+
 from __future__ import absolute_import, division
-from collections import namedtuple, OrderedDict
+from collections import OrderedDict
 from importlib import import_module
 import logging
 import os
@@ -42,18 +43,6 @@
 )
 
 
-PatientInfo = namedtuple("PatientInfo", (
-    "patient_id",
-    "vcf_paths",
-    "bam_path",
-    "mhc_alleles",
-    "num_somatic_variants",
-    "num_coding_effect_variants",
-    "num_variants_with_rna_support",
-    "num_variants_with_vaccine_peptides",
-))
-
-
 class TemplateDataCreator(object):
     def __init__(
             self,
diff --git a/vaxrank/vaccine_peptide.py b/vaxrank/vaccine_peptide.py
index a8785c0..4aeefe6 100644
--- a/vaxrank/vaccine_peptide.py
+++ b/vaxrank/vaccine_peptide.py
@@ -1,5 +1,3 @@
-# Copyright (c) 2016. Mount Sinai School of Medicine
-#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -15,60 +13,58 @@
 
 from __future__ import absolute_import, print_function, division
 
-from collections import namedtuple
 from operator import attrgetter
 
 import numpy as np
+from serializable import Serializable
 
 from .manufacturability import ManufacturabilityScores
 
-VaccinePeptideBase = namedtuple(
-    "VaccinePeptide", [
-        "mutant_protein_fragment",
-        "mutant_epitope_predictions",
-        "wildtype_epitope_predictions",
-        "mutant_epitope_score",
-        "wildtype_epitope_score",
-        "num_mutant_epitopes_to_keep",
-        "manufacturability_scores"])
-
 
-class VaccinePeptide(VaccinePeptideBase):
+class VaccinePeptide(Serializable):
     """
     VaccinePeptide combines the sequence information of MutantProteinFragment
     with MHC binding predictions for subsequences of the protein fragment.
 
-    The resulting lists of mutant and wildtype epitope predictions are sorted by ic50.
+    The resulting lists of mutant and wildtype epitope predictions
+    are sorted by affinity.
     """
-    def __new__(
-            cls,
+
+    def __init__(
+            self,
             mutant_protein_fragment,
             epitope_predictions,
-            num_mutant_epitopes_to_keep=10000):
+            num_mutant_epitopes_to_keep=10000,
+            sort_predictions_by='ic50'):
+        self.mutant_protein_fragment = mutant_protein_fragment
+        self.epitope_predictions = epitope_predictions
+        self.num_mutant_epitopes_to_keep = num_mutant_epitopes_to_keep
+        self.sort_predictions_by = sort_predictions_by
+
+        sort_key = attrgetter(sort_predictions_by)
+
         # only keep the top k epitopes
-        mutant_epitope_predictions = sorted([
-            p for p in epitope_predictions if p.overlaps_mutation and not p.occurs_in_reference
-        ], key=attrgetter('ic50'))[:num_mutant_epitopes_to_keep]
-        wildtype_epitope_predictions = sorted([
-            p for p in epitope_predictions if not p.overlaps_mutation or p.occurs_in_reference
-        ], key=attrgetter('ic50'))
-
-        wildtype_epitope_score = sum(
-            p.logistic_epitope_score() for p in wildtype_epitope_predictions)
+        self.mutant_epitope_predictions = sorted([
+            p for p in epitope_predictions
+            if p.overlaps_mutation and not p.occurs_in_reference
+        ], key=sort_key)[:self.num_mutant_epitopes_to_keep]
+
+        self.wildtype_epitope_predictions = sorted([
+            p for p in epitope_predictions
+            if not p.overlaps_mutation or p.occurs_in_reference
+        ], key=sort_key)
+
+        self.wildtype_epitope_score = sum(
+            p.logistic_epitope_score()
+            for p in self.wildtype_epitope_predictions)
         # only keep the top k epitopes for the purposes of the score
-        mutant_epitope_score = sum(
-            p.logistic_epitope_score() for p in mutant_epitope_predictions)
-
-        return VaccinePeptideBase.__new__(
-            cls,
-            mutant_protein_fragment=mutant_protein_fragment,
-            mutant_epitope_predictions=mutant_epitope_predictions,
-            wildtype_epitope_predictions=wildtype_epitope_predictions,
-            mutant_epitope_score=mutant_epitope_score,
-            wildtype_epitope_score=wildtype_epitope_score,
-            num_mutant_epitopes_to_keep=num_mutant_epitopes_to_keep,
-            manufacturability_scores=ManufacturabilityScores.from_amino_acids(
-                mutant_protein_fragment.amino_acids))
+        self.mutant_epitope_score = sum(
+            p.logistic_epitope_score()
+            for p in self.mutant_epitope_predictions)
+
+        self.manufacturability_scores = \
+            ManufacturabilityScores.from_amino_acids(
+                self.mutant_protein_fragment.amino_acids)
 
     def peptide_synthesis_difficulty_score_tuple(
             self,
@@ -207,4 +203,12 @@ def to_dict(self):
             "mutant_protein_fragment": self.mutant_protein_fragment,
             "epitope_predictions": epitope_predictions,
             "num_mutant_epitopes_to_keep": self.num_mutant_epitopes_to_keep,
+            "sort_predictions_by": self.sort_predictions_by,
         }
+
+    @classmethod
+    def from_dict(cls, d):
+        d = d.copy()
+        if "sort_predictions_by" not in d:
+            d["sort_predictions_by"] = "ic50"
+        return cls(**d)