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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def predict_from_sequences(self, sequences):
 """ Predict MHC ligands for sub-sequences of each input sequence. Parameters sequences : list of str Multiple amino acid sequences (without any names or IDs) Returns DataFrame with the following fields: - source_sequence - peptide - peptide_offset - peptide_length - allele - affinity - percentile_rank - prediction_method_name """

        # make each sequence its own unique ID
        sequence_dict = {
            seq: seq
            for seq in sequences
        }
        df = self.predict_from_named_sequences(sequence_dict)
        return df.rename(columns={"source_sequence_name": "source_sequence"})